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A Bayesian-Based Controller for Snake Robot Locomotion in Unstructured Environments | https://ieeexplore.ieee.org/document/9340722/ | [
"Yuanyuan Jia",
"Shugen Ma",
"Yuanyuan Jia",
"Shugen Ma"
] | This paper presents a novel Bayesian-based controller for snake robots in cluttered environment. It extends the conventional shape-based compliant control into statistical field providing an explicit mathematical formulation with Bayesian network. A sequential density propagation rule is derived by introducing several probability densities in a unified framework. Specifically, two input influence ... |
Learning to Locomote with Artificial Neural-Network and CPG-based Control in a Soft Snake Robot | https://ieeexplore.ieee.org/document/9340763/ | [
"Xuan Liu",
"Renato Gasoto",
"Ziyi Jiang",
"Cagdas Onal",
"Jie Fu",
"Xuan Liu",
"Renato Gasoto",
"Ziyi Jiang",
"Cagdas Onal",
"Jie Fu"
] | In this paper, we present a new locomotion control method for soft robot snakes. Inspired by biological snakes, our control architecture is composed of two key modules: A reinforcement learning (RL) module for achieving adaptive goal-tracking behaviors with changing goals, and a central pattern generator (CPG) system with Matsuoka oscillators for generating stable and diverse locomotion patterns. ... |
The Omega Turn: A Biologically-Inspired Turning Strategy for Elongated Limbless Robots | https://ieeexplore.ieee.org/document/9340872/ | [
"Tianyu Wang",
"Baxi Chong",
"Kelimar Diaz",
"Julian Whitman",
"Hang Lu",
"Matthew Travers",
"Daniel I. Goldman",
"Howie Choset",
"Tianyu Wang",
"Baxi Chong",
"Kelimar Diaz",
"Julian Whitman",
"Hang Lu",
"Matthew Travers",
"Daniel I. Goldman",
"Howie Choset"
] | Snake robots have the potential to locomote through tightly packed spaces, but turning effectively within unmodelled and unsensed environments remains challenging. Inspired by a behavior observed in the tiny nematode worm C. elegans, we propose a novel in-place turning gait for elongated limbless robots. To simplify the control of the robots' many internal degrees-of-freedom, we introduce a biolog... |
Bio-inspired Inverted Landing Strategy in a Small Aerial Robot Using Policy Gradient | https://ieeexplore.ieee.org/document/9341732/ | [
"Pan Liu",
"Junyi Geng",
"Yixian Li",
"Yanran Cao",
"Yagiz E. Bayiz",
"Jack W. Langelaan",
"Bo Cheng",
"Pan Liu",
"Junyi Geng",
"Yixian Li",
"Yanran Cao",
"Yagiz E. Bayiz",
"Jack W. Langelaan",
"Bo Cheng"
] | Landing upside down on a ceiling is challenging as it requires a flier to invert its body and land against the gravity, a process that demands a stringent spatiotemporal coordination of body translational and rotational motion. Although such an aerobatic feat is routinely performed by biological fliers such as flies, it is not yet achieved in aerial robots using onboard sensors. This work describe... |
A Bio-Inspired Framework for Joint Angle Estimation from Non-Collocated Sensors in Tendon-driven Systems | https://ieeexplore.ieee.org/document/9341268/ | [
"Daniel A. Hagen",
"Ali Marjaninejad",
"Francisco J. Valero-Cuevas",
"Daniel A. Hagen",
"Ali Marjaninejad",
"Francisco J. Valero-Cuevas"
] | Estimates of limb posture are critical for the control of robotic systems. This is generally accomplished by utilizing on-location joint angle encoders which may complicate the design, increase limb inertia, and add noise to the system. Conversely, some innovative or smaller robotic morphologies can benefit from non-collocated sensors when encoder size becomes prohibitively larger or the joints ar... |
Biomimetic Control Scheme for Musculoskeletal Humanoids Based on Motor Directional Tuning in the Brain | https://ieeexplore.ieee.org/document/9340896/ | [
"Yasunori Toshimitsu",
"Kento Kawaharazuka",
"Kei Tsuzuki",
"Moritaka Onitsuka",
"Manabu Nishiura",
"Yuya Koga",
"Yusuke Omura",
"Motoki Tomita",
"Yuki Asano",
"Kei Okada",
"Koji Kawasaki",
"Masayuki Inaba",
"Yasunori Toshimitsu",
"Kento Kawaharazuka",
"Kei Tsuzuki",
"Moritaka Onitsuka",
"Manabu Nishiura",
"Yuya Koga",
"Yusuke Omura",
"Motoki Tomita",
"Yuki Asano",
"Kei Okada",
"Koji Kawasaki",
"Masayuki Inaba"
] | In this research, we have taken a biomimetic approach to the control of musculoskeletal humanoids. A controller was designed based on the motor directional tuning phenomenon seen in the motor cortex of primates. Despite the simple implementation of the control scheme, complex coordinated movements such as reaching for target objects with its upper body was achieved, and is demonstrated in the acco... |
Development and Analysis of Digging and Soil Removing Mechanisms for Mole-Bot: Bio-Inspired Mole-Like Drilling Robot | https://ieeexplore.ieee.org/document/9341230/ | [
"Junseok Lee",
"Christian Tirtawardhana",
"Hyun Myung",
"Junseok Lee",
"Christian Tirtawardhana",
"Hyun Myung"
] | Interests in exploration of new energy resources are increasing due to the exhaustion of existing resources. To explore new energy sources, various studies have been conducted to improve the drilling performance of drilling equipment for deep and strong ground. However, with better performance, the modern drilling equipment is bulky and, furthermore, has become inconvenient in both installation an... |
A Bio–inspired Quadruped Robot Exploiting Flexible Shoulder for Stable and Efficient Walking | https://ieeexplore.ieee.org/document/9341444/ | [
"Akira Fukuhara",
"Megu Gunji",
"Yoichi Masuda",
"Kenjiro Tadakuma",
"Akio Ishiguro",
"Akira Fukuhara",
"Megu Gunji",
"Yoichi Masuda",
"Kenjiro Tadakuma",
"Akio Ishiguro"
] | While most modern-day quadruped robots crouch their limbs during the stance phase to stabilize the trunk, mammals exploit the inverted-pendulum motions of their limbs and realize both efficient and stable walking. Although the flexibility of the shoulder region of mammals is expected to contribute to reconciling the discrepancy between the forelimbs and hindlimbs for natural walking, the complex b... |
An Earthworm-like Soft Robot with Integration of Single Pneumatic Actuator and Cellular Structures for Peristaltic Motion | https://ieeexplore.ieee.org/document/9341166/ | [
"Mingcan Liu",
"Zhaoyi Xu",
"Jing Jie Ong",
"Jian Zhu",
"Wen Feng Lu",
"Mingcan Liu",
"Zhaoyi Xu",
"Jing Jie Ong",
"Jian Zhu",
"Wen Feng Lu"
] | Earthworm-like soft robots have been widely studied for various applications, such as medical endoscopy and pipeline inspection. Many actuation modes have been chosen to drive the soft robots, including pneumatic actuators, dielectric elastomeric actuators, and shape memory actuators. Pneumatic actuators stand out since the soft robots with pneumatic actuation can produce relatively large forces a... |
Development of a Maneuverable Un-Tethered Multi-fin Soft Robot | https://ieeexplore.ieee.org/document/9341093/ | [
"T.V. Truong",
"R.C. Mysa",
"T. Stalin",
"P.M. Aby Raj",
"P. Valdivia y Alvarado",
"T.V. Truong",
"R.C. Mysa",
"T. Stalin",
"P.M. Aby Raj",
"P. Valdivia y Alvarado"
] | In this paper, the design, fabrication, numerical studies, and preliminary characterization of a multi-fin soft robot are presented. The design is simple, robust, and fully autonomous. The robot has a 216mm body length and displays great potential to achieve uncoupled surge (forwards and backwards), sway, and heave motions. Computational fluid dynamic (CFD) studies are employed to evaluate appropr... |
Emergence of Swing-to-Stance Transition from Interlocking Mechanism in Horse Hindlimb | https://ieeexplore.ieee.org/document/9341026/ | [
"Kazuhiro Miyashita",
"Yoichi Masuda",
"Megu Gunji",
"Akira Fukuhara",
"Kenjiro Tadakuma",
"Masato Ishikawa",
"Kazuhiro Miyashita",
"Yoichi Masuda",
"Megu Gunji",
"Akira Fukuhara",
"Kenjiro Tadakuma",
"Masato Ishikawa"
] | The bodies of quadrupeds have very complex muscle-tendon structure. In particular, it is known that in the horse hindlimb, multiple joints in the leg are remarkably interlocked due to the muscle-tendon structure. Although the function of these interlocking mechanisms during standing has been investigated in the field of anatomy, the function related to the emergence of limb trajectory during dynam... |
Emergent adaptive gait generation through Hebbian sensor-motor maps by morphological probing | https://ieeexplore.ieee.org/document/9341211/ | [
"Matthieu Dujany",
"Simon Hauser",
"Mehmet Mutlu",
"Martijn van der Sar",
"Jonathan Arreguit",
"Takeshi Kano",
"Akio Ishiguro",
"Auke Ijspeert",
"Matthieu Dujany",
"Simon Hauser",
"Mehmet Mutlu",
"Martijn van der Sar",
"Jonathan Arreguit",
"Takeshi Kano",
"Akio Ishiguro",
"Auke Ijspeert"
] | Gait emergence and adaptation in animals is unmatched in robotic systems. Animals can create and recover locomotive functions "on-the-fly" after an injury whereas locomotion controllers for robots lack robustness to morphological changes. In this work, we extend previous research on emergent interlimb coordination of legged robots based on coupled phase oscillators with force feedback terms. We in... |
Soft Microrobotic Transmissions Enable Rapid Ground-Based Locomotion | https://ieeexplore.ieee.org/document/9341114/ | [
"Wei Zhou",
"Nick Gravish",
"Wei Zhou",
"Nick Gravish"
] | In this paper we present the design, fabrication, testing, and control of a 0.4 g milliscale robot employing a soft polymer flexure transmission for rapid ground movement. The robot was constructed through a combination of two methods: smart-composite-manufacturing (SCM) process to fabricate the actuators and robot chassis, and silicone elastomer molding and casting to fabricate a soft flexure tra... |
An Untethered 216-mg Insect-Sized Jumping Robot with Wireless Power Transmission | https://ieeexplore.ieee.org/document/9341238/ | [
"Riccy Kurniawan",
"Tamaki Fukudome",
"Hao Qiu",
"Makoto Takamiya",
"Yoshihiro Kawahara",
"Jinkyu Yang",
"Ryuma Niiyama",
"Riccy Kurniawan",
"Tamaki Fukudome",
"Hao Qiu",
"Makoto Takamiya",
"Yoshihiro Kawahara",
"Jinkyu Yang",
"Ryuma Niiyama"
] | We present the first demonstration of a battery-free untethered wirelessly powered sub-gram jumping robot on an insect-scale. In order to operate the insect-sized robot autonomously, the limitation in battery use emphasizes the need for a wireless power transmission system as an onboard power solution. We designed a wireless power transmission system based on inductive coupling to power the Shape ... |
Cooperative Simultaneous Tracking and Jamming for Disabling a Rogue Drone | https://ieeexplore.ieee.org/document/9340835/ | [
"Savvas Papaioannou",
"Panayiotis Kolios",
"Christos G. Panayiotou",
"Marios M. Polycarpou",
"Savvas Papaioannou",
"Panayiotis Kolios",
"Christos G. Panayiotou",
"Marios M. Polycarpou"
] | This work investigates the problem of simultaneous tracking and jamming of a rogue drone in 3D space with a team of cooperative unmanned aerial vehicles (UAVs). We propose a decentralized estimation, decision and control framework in which a team of UAVs cooperate in order to a) optimally choose their mobility control actions that result in accurate target tracking and b) select the desired transm... |
SpCoMapGAN: Spatial Concept Formation-based Semantic Mapping with Generative Adversarial Networks | https://ieeexplore.ieee.org/document/9341456/ | [
"Yuki Katsumata",
"Akira Taniguchi",
"Lotfi El Hafi",
"Yoshinobu Hagiwara",
"Tadahiro Taniguchi",
"Yuki Katsumata",
"Akira Taniguchi",
"Lotfi El Hafi",
"Yoshinobu Hagiwara",
"Tadahiro Taniguchi"
] | In semantic mapping, which connects semantic information to an environment map, it is a challenging task for robots to deal with both local and global information of environments. In addition, it is important to estimate semantic information of unobserved areas from already acquired partial observations in a newly visited environment. On the other hand, previous studies on spatial concept formatio... |
To Ask or Not to Ask: A User Annoyance Aware Preference Elicitation Framework for Social Robots | https://ieeexplore.ieee.org/document/9341607/ | [
"Balint Gucsi",
"Danesh S. Tarapore",
"William Yeoh",
"Christopher Amato",
"Long Tran-Thanh",
"Balint Gucsi",
"Danesh S. Tarapore",
"William Yeoh",
"Christopher Amato",
"Long Tran-Thanh"
] | In this paper we investigate how social robots can efficiently gather user preferences without exceeding the allowed user annoyance threshold. To do so, we use a Gazebo based simulated office environment with a TIAGo Steel robot. We then formulate the user annoyance aware preference elicitation problem as a combination of tensor completion and knapsack problems. We then test our approach on the af... |
Visual Task Progress Estimation with Appearance Invariant Embeddings for Robot Control and Planning | https://ieeexplore.ieee.org/document/9341443/ | [
"Guilherme Maeda",
"Joni Väätäinen",
"Hironori Yoshida",
"Guilherme Maeda",
"Joni Väätäinen",
"Hironori Yoshida"
] | One of the challenges of full autonomy is to have robots capable of manipulating its current environment to achieve another environment configuration. This paper is a step towards this challenge, focusing on the visual understanding of the task. Our approach trains a deep neural network to represent images as measurable features that are useful to estimate the progress (or phase) of a task. The tr... |
Lane-Attention: Predicting Vehicles’ Moving Trajectories by Learning Their Attention Over Lanes | https://ieeexplore.ieee.org/document/9341233/ | [
"Jiacheng Pan",
"Hongyi Sun",
"Kecheng Xu",
"Yifei Jiang",
"Xiangquan Xiao",
"Jiangtao Hu",
"Jinghao Miao",
"Jiacheng Pan",
"Hongyi Sun",
"Kecheng Xu",
"Yifei Jiang",
"Xiangquan Xiao",
"Jiangtao Hu",
"Jinghao Miao"
] | Accurately forecasting the future movements of surrounding vehicles is essential for safe and efficient operations of autonomous driving cars. This task is difficult because a vehicle's moving trajectory is greatly determined by its driver's intention, which is often hard to estimate. By leveraging attention mechanisms along with long short-term memory (LSTM) networks, this work learns the relatio... |
Pedestrian Intention Prediction for Autonomous Driving Using a Multiple Stakeholder Perspective Model | https://ieeexplore.ieee.org/document/9341083/ | [
"Kyungdo Kim",
"Yoon Kyung Lee",
"Hyemin Ahn",
"Sowon Hahn",
"Songhwai Oh",
"Kyungdo Kim",
"Yoon Kyung Lee",
"Hyemin Ahn",
"Sowon Hahn",
"Songhwai Oh"
] | This paper proposes a multiple stakeholder perspective model (MSPM) which predicts the future pedestrian trajectory observed from vehicle's point of view. For the vehicle-pedestrian interaction, the estimation of the pedestrian's intention is a key factor. However, even if this interaction is commonly initiated by both the human (pedestrian) and the agent (driver), current research focuses on deve... |
Computing High-Quality Clutter Removal Solutions for Multiple Robots | https://ieeexplore.ieee.org/document/9341144/ | [
"Wei N. Tang",
"Shuai D. Han",
"Jingjin Yu",
"Wei N. Tang",
"Shuai D. Han",
"Jingjin Yu"
] | We investigate the task and motion planning problem of clearing clutter from a workspace with limited ingress/egress access for multiple robots. We call the problem multi-robot clutter removal (MRCR). Targeting practical applications where motion planning is non-trivial but is not a bottle-neck, we focus on finding high-quality solutions for feasible MRCR instances, which depends on the ability to... |
Adaptive Partitioning for Coordinated Multi-agent Perimeter Defense | https://ieeexplore.ieee.org/document/9341417/ | [
"Douglas G. Macharet",
"Austin K. Chen",
"Daigo Shishika",
"George J. Pappas",
"Vijay Kumar",
"Douglas G. Macharet",
"Austin K. Chen",
"Daigo Shishika",
"George J. Pappas",
"Vijay Kumar"
] | Multi-Robot Systems have been recently employed in different applications and have advantages over single-robot systems, such as increased robustness and task performance efficiency. We consider such assemblies specifically in the scenario of perimeter defense, where the task is to defend a circular perimeter by intercepting radially approaching targets. Possible intruders appear randomly at a fix... |
Approximated Dynamic Trait Models for Heterogeneous Multi-Robot Teams | https://ieeexplore.ieee.org/document/9341107/ | [
"Glen Neville",
"Harish Ravichandar",
"Kenneth Shaw",
"Sonia Chernova",
"Glen Neville",
"Harish Ravichandar",
"Kenneth Shaw",
"Sonia Chernova"
] | To realize effective heterogeneous multi-agent teams, we must be able to leverage individual agents' relative strengths. Recent work has addressed this challenge by introducing trait-based task assignment approaches that exploit the agents' relative advantages. These approaches, however, assume that the agents' traits remain static. Indeed, in real-world scenarios, traits are likely to vary as age... |
Cooperative Control of Mobile Robots with Stackelberg Learning | https://ieeexplore.ieee.org/document/9341376/ | [
"Joewie J. Koh",
"Guohui Ding",
"Christoffer Heckman",
"Lijun Chen",
"Alessandro Roncone",
"Joewie J. Koh",
"Guohui Ding",
"Christoffer Heckman",
"Lijun Chen",
"Alessandro Roncone"
] | Multi-robot cooperation requires agents to make decisions that are consistent with the shared goal without disregarding action-specific preferences that might arise from asymmetry in capabilities and individual objectives. To accomplish this goal, we propose a method named SLiCC: Stackelberg Learning in Cooperative Control. SLiCC models the problem as a partially observable stochastic game compose... |
Sparse Discrete Communication Learning for Multi-Agent Cooperation Through Backpropagation | https://ieeexplore.ieee.org/document/9341079/ | [
"Benjamin Freed",
"Rohan James",
"Guillaume Sartoretti",
"Howie Choset",
"Benjamin Freed",
"Rohan James",
"Guillaume Sartoretti",
"Howie Choset"
] | Recent approaches to multi-agent reinforcement learning (MARL) with inter-agent communication have often overlooked important considerations of real-world communication networks, such as limits on bandwidth. In this paper, we propose an approach to learning sparse discrete communication through backpropagation in the context of MARL, in which agents are incentivized to communicate as little as pos... |
Multi-Robot Coordinated Planning in Confined Environments under Kinematic Constraints | https://ieeexplore.ieee.org/document/9341213/ | [
"Clayton Mangette",
"Pratap Tokekar",
"Clayton Mangette",
"Pratap Tokekar"
] | We investigate the problem of multi-robot coordinated planning in environments where the robots may have to operate in close proximity to each other. We seek computationally efficient planners that ensure safe paths and adherence to kinematic constraints. We extend the central planner dRRT* with our variant, fast-dRRT (fdRRT), with the intention being to use in tight environments that lead to a hi... |
SwarmLab: a Matlab Drone Swarm Simulator | https://ieeexplore.ieee.org/document/9340854/ | [
"Enrica Soria",
"Fabrizio Schiano",
"Dario Floreano",
"Enrica Soria",
"Fabrizio Schiano",
"Dario Floreano"
] | Among the available solutions for drone swarm simulations, we identified a lack of simulation frameworks that allow easy algorithms prototyping, tuning, debugging and performance analysis. Moreover, users who want to dive in the research field of drone swarms often need to interface with multiple programming languages. We present SwarmLab, a software entirely written in MATLAB, that aims at the cr... |
An Actor-based Programming Framework for Swarm Robotic Systems | https://ieeexplore.ieee.org/document/9341198/ | [
"Wei Yi",
"Bin Di",
"Ruihao Li",
"Huadong Dai",
"Xiaodong Yi",
"Yanzhen Wang",
"Xuejun Yang",
"Wei Yi",
"Bin Di",
"Ruihao Li",
"Huadong Dai",
"Xiaodong Yi",
"Yanzhen Wang",
"Xuejun Yang"
] | Programming cooperative tasks for autonomous swarm robotic systems has always been challenging. In this paper, we introduce a concept ‘Actor’, as a virtualization for robot platforms. Every robot platform in the swarm robotic system carries out the task and interacts with others as an Actor. We designed an Actor-based framework for the management of autonomous swarm robotic systems including modul... |
A Distributed Range-Only Collision Avoidance Approach for Low-cost Large-scale Multi-Robot Systems | https://ieeexplore.ieee.org/document/9341539/ | [
"Ruihua Han",
"Shengduo Chen",
"Qi Hao",
"Ruihua Han",
"Shengduo Chen",
"Qi Hao"
] | The challenges of developing low-cost, large-scale multi-robot navigation systems include noisy measurements, a large number of robots, and computing efficiency for collision avoidance. This paper presents a distributed motion planning framework for a large number of robots to navigate with robust collision avoidance using low-cost range only measurements. The novelty of this work is threefold. (1... |
Automatic Control Synthesis for Swarm Robots from Formation and Location-based High-level Specifications | https://ieeexplore.ieee.org/document/9341466/ | [
"Ji Chen",
"Hanlin Wang",
"Michael Rubenstein",
"Hadas Kress-Gazit",
"Ji Chen",
"Hanlin Wang",
"Michael Rubenstein",
"Hadas Kress-Gazit"
] | In this paper, we propose an abstraction that captures high-level formation and location-based swarm behaviors, and an automated control synthesis framework to generate correct-by-construction behaviors. Our abstraction includes symbols representing both possible formations and physical locations in the workspace. We allow users to write linear temporal logic (LTL) specifications over the symbols ... |
Low-viewpoint forest depth dataset for sparse rover swarms | https://ieeexplore.ieee.org/document/9341435/ | [
"Chaoyue Niu",
"Danesh Tarapore",
"Klaus-Peter Zauner",
"Chaoyue Niu",
"Danesh Tarapore",
"Klaus-Peter Zauner"
] | Rapid progress in embedded computing hardware increasingly enables on-board image processing on small robots. This development opens the path to replacing costly sensors with sophisticated computer vision techniques. A case in point is the prediction of scene depth information from a monocular camera for autonomous navigation. Motivated by the aim to develop a robot swarm suitable for sensing, mon... |
Indoor Scene Recognition in 3D | https://ieeexplore.ieee.org/document/9341580/ | [
"Shengyu Huang",
"Mikhail Usvyatsov",
"Konrad Schindler",
"Shengyu Huang",
"Mikhail Usvyatsov",
"Konrad Schindler"
] | Recognising in what type of environment one is located is an important perception task. For instance, for a robot operating indoors it is helpful to be aware whether it is in a kitchen, a hallway or a bedroom. Existing approaches attempt to classify the scene based on 2D images or 2.5D range images. Here, we study scene recognition from 3D point cloud (or voxel) data, and show that it greatly outp... |
QSRNet: Estimating Qualitative Spatial Representations from RGB-D Images | https://ieeexplore.ieee.org/document/9341452/ | [
"Sang Uk Lee",
"Sungkweon Hong",
"Andreas Hofmann",
"Brian Williams",
"Sang Uk Lee",
"Sungkweon Hong",
"Andreas Hofmann",
"Brian Williams"
] | Humans perceive and describe their surroundings with qualitative statements (e.g., "Alice's hand is in contact with a bottle."), rather than quantitative values (e.g., 6-D poses of Alice's hand and a bottle). Qualitative spatial representation (QSR) is a framework that represents the spatial information of objects in a qualitative manner. Region connection calculus (RCC), qualitative trajectory ca... |
Acquiring Mechanical Knowledge from 3D Point Clouds | https://ieeexplore.ieee.org/document/9341558/ | [
"Zijia Li",
"Kei Okada",
"Masayuki Inaba",
"Zijia Li",
"Kei Okada",
"Masayuki Inaba"
] | We consider the problem of acquiring mechanical knowledge through visual cues to help robots use objects in new situations. In this work, we propose a novel deep learning approach that allows a robot to acquire mechanical knowledge from 3D point clouds. This presents two main challenges. The first challenge is that a robot needs to infer novel objects' functions from its experience. Secondly, the ... |
Learning visual policies for building 3D shape categories | https://ieeexplore.ieee.org/document/9341750/ | [
"Alexander Pashevich",
"Igor Kalevatykh",
"Ivan Laptev",
"Cordelia Schmid",
"Alexander Pashevich",
"Igor Kalevatykh",
"Ivan Laptev",
"Cordelia Schmid"
] | Manipulation and assembly tasks require non-trivial planning of actions depending on the environment and the final goal. Previous work in this domain often assembles particular instances of objects from known sets of primitives. In contrast, we aim to handle varying sets of primitives and to construct different objects of a shape category. Given a single object instance of a category, e.g. an arch... |
The Robot as Scientist: Using Mental Simulation to Test Causal Hypotheses Extracted from Human Activities in Virtual Reality | https://ieeexplore.ieee.org/document/9341505/ | [
"Constantin Uhde",
"Nicolas Berberich",
"Karinne Ramirez-Amaro",
"Gordon Cheng",
"Constantin Uhde",
"Nicolas Berberich",
"Karinne Ramirez-Amaro",
"Gordon Cheng"
] | To act effectively in its environment, a cognitive robot needs to understand the causal dependencies of all intermediate actions leading up to its goal. For example, the system has to infer that it is instrumental to open a cupboard door before trying to grasp an object inside the cupboard. In this paper, we introduce a novel learning method for extracting instrumental dependencies by following th... |
Learning Transition Models with Time-delayed Causal Relations | https://ieeexplore.ieee.org/document/9340809/ | [
"Junchi Liang",
"Abdeslam Boularias",
"Junchi Liang",
"Abdeslam Boularias"
] | This paper introduces an algorithm for discovering implicit and delayed causal relations between events observed by a robot at arbitrary times, with the objective of improving data-efficiency and interpretability of model- based reinforcement learning (RL) techniques. The proposed algorithm initially predicts observations with the Markov assumption, and incrementally introduces new hidden variable... |
Going Cognitive: A Demonstration of the Utility of Task-General Cognitive Architectures for Adaptive Robotic Task Performance | https://ieeexplore.ieee.org/document/9340863/ | [
"Tyler Frasca",
"Zhao Han",
"Jordan Allspaw",
"Holly Yanco",
"Matthias Scheutz",
"Tyler Frasca",
"Zhao Han",
"Jordan Allspaw",
"Holly Yanco",
"Matthias Scheutz"
] | It has been claimed that a main advantage of cognitive architectures (compared to other types of specialized robotic architectures) is that they are task-general and can thus learn to perform any task as long as they have the right perceptual and action primitives. In this paper, we provide empirical evidence for this claim by directly comparing a high-performing custom robotic architecture develo... |
Uncertainty-aware Self-supervised 3D Data Association | https://ieeexplore.ieee.org/document/9341251/ | [
"Jianren Wang",
"Siddharth Ancha",
"Yi-Ting Chen",
"David Held",
"Jianren Wang",
"Siddharth Ancha",
"Yi-Ting Chen",
"David Held"
] | 3D object trackers usually require training on large amounts of annotated data that is expensive and time-consuming to collect. Instead, we propose leveraging vast unlabeled datasets by self-supervised metric learning of 3D object trackers, with a focus on data association. Large scale annotations for unlabeled data are cheaply obtained by automatic object detection and association across frames. ... |
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking | https://ieeexplore.ieee.org/document/9341120/ | [
"Hao Zou",
"Jinhao Cui",
"Xin Kong",
"Chujuan Zhang",
"Yong Liu",
"Feng Wen",
"Wanlong Li",
"Hao Zou",
"Jinhao Cui",
"Xin Kong",
"Chujuan Zhang",
"Yong Liu",
"Feng Wen",
"Wanlong Li"
] | This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant search space. A main challenge in 3D single object tracking is how to reduce search space for generating appropriate 3D candidates. Instead of solely relying on 3D proposals, firstly, our method leverages the Siamese net... |
Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise | https://ieeexplore.ieee.org/document/9341386/ | [
"Ozan Çatal",
"Sam Leroux",
"Cedric De Boom",
"Tim Verbelen",
"Bart Dhoedt",
"Ozan Çatal",
"Sam Leroux",
"Cedric De Boom",
"Tim Verbelen",
"Bart Dhoedt"
] | As warehouses, storage facilities and factories become more expanded and equipped with smart devices, there is a substantial need for rapid, intelligent and autonomous detection of unusual and potentially hazardous situations, also called anomalies. In particular for Autonomous Guided Vehicles (AGVs) that drive around these premises independently, unforeseen obstructions along their path-e.g. a ca... |
3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction | https://ieeexplore.ieee.org/document/9341671/ | [
"Shuaihang Yuan",
"Xiang Li",
"Anthony Tzes",
"Yi Fang",
"Shuaihang Yuan",
"Xiang Li",
"Anthony Tzes",
"Yi Fang"
] | This paper deals with predicting future 3D motions of 3D object scans from the previous two consecutive frames. Previous methods mostly focus on sparse motion prediction in the form of skeletons. While in this paper, we focus on predicting dense 3D motions in the form of 3D point clouds. To approach this problem, we propose a self-supervised approach that leverages the power of the deep neural net... |
Learning Vision-Based Physics Intuition Models for Non-Disruptive Object Extraction | https://ieeexplore.ieee.org/document/9341675/ | [
"Sarthak Ahuja",
"Henny Admoni",
"Aaron Steinfeld",
"Sarthak Ahuja",
"Henny Admoni",
"Aaron Steinfeld"
] | Robots operating in human environments must be careful, when executing their manipulation skills, not to disturb nearby objects. This requires robots to reason about the effect of their manipulation choices by accounting for the support relationships among objects in the scene. Humans do this in part by visually assessing their surroundings and using physics intuition for how likely it is that a p... |
Spectral-GANs for High-Resolution 3D Point-cloud Generation | https://ieeexplore.ieee.org/document/9341265/ | [
"Sameera Ramasinghe",
"Salman Khan",
"Nick Barnes",
"Stephen Gould",
"Sameera Ramasinghe",
"Salman Khan",
"Nick Barnes",
"Stephen Gould"
] | Point-clouds are a popular choice for robotics and computer vision tasks due to their accurate shape description and direct acquisition from range-scanners. This demands the ability to synthesize and reconstruct high-quality point-clouds. Current deep generative models for 3D data generally work on simplified representations (e.g., voxelized objects) and cannot deal with the inherent redundancy an... |
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models | https://ieeexplore.ieee.org/document/9340732/ | [
"Varun Ravi Kumar",
"Senthil Yogamani",
"Markus Bach",
"Christian Witt",
"Stefan Milz",
"Patrick Mäder",
"Varun Ravi Kumar",
"Senthil Yogamani",
"Markus Bach",
"Christian Witt",
"Stefan Milz",
"Patrick Mäder"
] | In classical computer vision, rectification is an integral part of multi-view depth estimation. It typically includes epipolar rectification and lens distortion correction. This process simplifies the depth estimation significantly, and thus it has been adopted in CNN approaches. However, rectification has several side effects, including a reduced field of view (FOV), resampling distortion, and se... |
AutoLay: Benchmarking amodal layout estimation for autonomous driving | https://ieeexplore.ieee.org/document/9341724/ | [
"Kaustubh Mani",
"N. Sai Shankar",
"Krishna Murthy Jatavallabhula",
"K. Madhava Krishna",
"Kaustubh Mani",
"N. Sai Shankar",
"Krishna Murthy Jatavallabhula",
"K. Madhava Krishna"
] | Given an image or a video captured from a monocular camera, amodal layout estimation is the task of predicting semantics and occupancy in bird's eye view. The term amodal implies we also reason about entities in the scene that are occluded or truncated in image space. While several recent efforts have tackled this problem, there is a lack of standardization in task specification, datasets, and eva... |
Data-driven Distributed State Estimation and Behavior Modeling in Sensor Networks | https://ieeexplore.ieee.org/document/9340838/ | [
"Rui Yu",
"Zhenyuan Yuan",
"Minghui Zhu",
"Zihan Zhou",
"Rui Yu",
"Zhenyuan Yuan",
"Minghui Zhu",
"Zihan Zhou"
] | Nowadays, the prevalence of sensor networks has enabled tracking of the states of dynamic objects for a wide spectrum of applications from autonomous driving to environmental monitoring and urban planning. However, tracking realworld objects often faces two key challenges: First, due to the limitation of individual sensors, state estimation needs to be solved in a collaborative and distributed man... |
ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation | https://ieeexplore.ieee.org/document/9340710/ | [
"Venkatraman Narayanan",
"Bala Murali Manoghar",
"Vishnu Sashank Dorbala",
"Dinesh Manocha",
"Aniket Bera",
"Venkatraman Narayanan",
"Bala Murali Manoghar",
"Vishnu Sashank Dorbala",
"Dinesh Manocha",
"Aniket Bera"
] | We present ProxEmo, a novel end-to-end emotion prediction algorithm for socially aware robot navigation among pedestrians. Our approach predicts the perceived emotions of a pedestrian from walking gaits, which is then used for emotion-guided navigation taking into account social and proxemic constraints. To classify emotions, we propose a multi-view skeleton graph convolution-based model that work... |
Semantic Graph Based Place Recognition for 3D Point Clouds | https://ieeexplore.ieee.org/document/9341060/ | [
"Xin Kong",
"Xuemeng Yang",
"Guangyao Zhai",
"Xiangrui Zhao",
"Xianfang Zeng",
"Mengmeng Wang",
"Yong Liu",
"Wanlong Li",
"Feng Wen",
"Xin Kong",
"Xuemeng Yang",
"Guangyao Zhai",
"Xiangrui Zhao",
"Xianfang Zeng",
"Mengmeng Wang",
"Yong Liu",
"Wanlong Li",
"Feng Wen"
] | Due to the difficulty in generating the effective descriptors which are robust to occlusion and viewpoint changes, place recognition for 3D point cloud remains an open issue. Unlike most of the existing methods that focus on extracting local, global, and statistical features of raw point clouds, our method aims at the semantic level that can be superior in terms of robustness to environmental chan... |
A Bottom-up Framework for Construction of Structured Semantic 3D Scene Graph | https://ieeexplore.ieee.org/document/9341228/ | [
"Bangguo Yu",
"Chongyu Chen",
"Fengyu Zhou",
"Fang Wan",
"Wenmi Zhuang",
"Yang Zhao",
"Bangguo Yu",
"Chongyu Chen",
"Fengyu Zhou",
"Fang Wan",
"Wenmi Zhuang",
"Yang Zhao"
] | For high-level human-robot interaction tasks, 3D scene understanding is important and non-trivial for autonomous robots. However, parsing and utilizing effective environment information of the 3D scene is not trivial due to the complexity of the 3D environment and the limited ability for reasoning about our visual world. Although there have been great efforts on semantic detection and scene analys... |
Autonomous Detection and Assessment with Moving Sensors | https://ieeexplore.ieee.org/document/9340997/ | [
"Steven J. Spencer",
"Anup Parikh",
"Daniel R. McArthur",
"Carol C. Young",
"Timothy J. Blada",
"Jonathon E. Slightam",
"Stephen P. Buerger",
"Steven J. Spencer",
"Anup Parikh",
"Daniel R. McArthur",
"Carol C. Young",
"Timothy J. Blada",
"Jonathon E. Slightam",
"Stephen P. Buerger"
] | Current approaches to physical security suffer from high false alarm rates and frequent human operator involvement, despite the relative rarity of real-world threats. We present a novel architecture for autonomous adaptive physical security called autonomous detection and assessment with moving sensors (ADAMS). ADAMS is a framework for reducing nuisance and false alarms by placing mobile robotic p... |
RegionNet: Region-feature-enhanced 3D Scene Understanding Network with Dual Spatial-aware Discriminative Loss | https://ieeexplore.ieee.org/document/9340725/ | [
"Guanghui Zhang",
"Dongchen Zhu",
"Xiaoqing Ye",
"Wenjun Shi",
"Minghong Chen",
"Jiamao Li",
"Xiaolin Zhang",
"Guanghui Zhang",
"Dongchen Zhu",
"Xiaoqing Ye",
"Wenjun Shi",
"Minghong Chen",
"Jiamao Li",
"Xiaolin Zhang"
] | Neural networks have recently achieved impressive success in semantic and instance segmentation on 2D images. However, their capabilities have not been fully explored to address semantic instance segmentation on unstructured 3D point cloud data. Digging into the regional feature representation to boost point cloud comprehension, we propose a region-feature-enhanced structure consisting of adaptive... |
Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks | https://ieeexplore.ieee.org/document/9341508/ | [
"Ferdinand Langer",
"Andres Milioto",
"Alexandre Haag",
"Jens Behley",
"Cyrill Stachniss",
"Ferdinand Langer",
"Andres Milioto",
"Alexandre Haag",
"Jens Behley",
"Cyrill Stachniss"
] | Inferring semantic information towards an understanding of the surrounding environment is crucial for autonomous vehicles to drive safely. Deep learning-based segmentation methods can infer semantic information directly from laser range data, even in the absence of other sensor modalities such as cameras. In this paper, we address improving the generalization capabilities of such deep learning mod... |
On a videoing control system based on object detection and tracking | https://ieeexplore.ieee.org/document/9341721/ | [
"Yanhao Ren",
"Yi Wang",
"Qi Tang",
"Haijun Jiang",
"Wenlian Lu",
"Yanhao Ren",
"Yi Wang",
"Qi Tang",
"Haijun Jiang",
"Wenlian Lu"
] | In this paper, we propose a camera control system towards occasionally videoing preassigned objects. Based on the technique of real-time visual detection and tracking, using the Kalman filter and re-identification (ReID), we propose continuous composition of lens, based on the atomic rules of shots, and give the trajectory planning of the camera, to generate the PID controller to the pan-tilt. By ... |
Understanding Dynamic Scenes using Graph Convolution Networks | https://ieeexplore.ieee.org/document/9341018/ | [
"Sravan Mylavarapu",
"Mahtab Sandhu",
"Priyesh Vijayan",
"K Madhava Krishna",
"Balaraman Ravindran",
"Anoop Namboodiri",
"Sravan Mylavarapu",
"Mahtab Sandhu",
"Priyesh Vijayan",
"K Madhava Krishna",
"Balaraman Ravindran",
"Anoop Namboodiri"
] | We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera. The input to MRGCN is a multi-relational graph where the graph's nodes represent the active and passive agents/objects in the scene, and the bidirectional edges that connect every pair of nod... |
Quadrotor-Enabled Autonomous Parking Occupancy Detection | https://ieeexplore.ieee.org/document/9341081/ | [
"Yafeng Wang",
"Beibei Ren",
"Yafeng Wang",
"Beibei Ren"
] | Large special-events parking involves various parking scenarios, e.g., temporary parking and on-street parking. Their occupancy detection is challenging as it is unrealistic to construct gates/stations for temporary parking areas or build a sensor-based detection system to cover every single street. To address this issue, this study develops a quadrotor-enabled autonomous parking occupancy detecti... |
Learning Consistency Pursued Correlation Filters for Real-Time UAV Tracking | https://ieeexplore.ieee.org/document/9340954/ | [
"Changhong Fu",
"Xiaoxiao Yang",
"Fan Li",
"Juntao Xu",
"Changjing Liu",
"Peng Lu",
"Changhong Fu",
"Xiaoxiao Yang",
"Fan Li",
"Juntao Xu",
"Changjing Liu",
"Peng Lu"
] | Correlation filter (CF)-based methods have demonstrated exceptional performance in visual object tracking for unmanned aerial vehicle (UAV) applications, but suffer from the undesirable boundary effect. To solve this issue, spatially regularized correlation filters (SRDCF) proposes the spatial regularization to penalize filter coefficients, thereby significantly improving the tracking performance.... |
Learning Soft Robotic Assembly Strategies from Successful and Failed Demonstrations | https://ieeexplore.ieee.org/document/9341504/ | [
"Masashi Hamaya",
"Felix von Drigalski",
"Takamitsu Matsubara",
"Kazutoshi Tanaka",
"Robert Lee",
"Chisato Nakashima",
"Yoshiya Shibata",
"Yoshihisa Ijiri",
"Masashi Hamaya",
"Felix von Drigalski",
"Takamitsu Matsubara",
"Kazutoshi Tanaka",
"Robert Lee",
"Chisato Nakashima",
"Yoshiya Shibata",
"Yoshihisa Ijiri"
] | Physically soft robots are promising for robotic assembly tasks as they allow stable contacts with the environment. In this study, we propose a novel learning system for soft robotic assembly strategies. We formulate this problem as a reinforcement learning task and design the reward function from human demonstrations. Our key insight is that the failed demonstrations can be used as constraints to... |
Pattern Analysis and Parameters Optimization of Dynamic Movement Primitives for Learning Unknown Trajectories | https://ieeexplore.ieee.org/document/9340702/ | [
"Mantian Li",
"Zeguo Yang",
"Fusheng Zha",
"Xin Wang",
"Pengfei Wang",
"Wei Guo",
"Darwin Caldwell",
"Fei Chen",
"Mantian Li",
"Zeguo Yang",
"Fusheng Zha",
"Xin Wang",
"Pengfei Wang",
"Wei Guo",
"Darwin Caldwell",
"Fei Chen"
] | A robot in the future may initially has a good learning capability but an empty library of movements. It gradually enriches its library of movements through human demonstrations. Dynamic Movement Primitives (DMPs) has been proved to be an effective way to represent trajectories. Trajectories are classified into discrete and rhythmic ones, and parameters are set for each demonstrated trajectory. Ho... |
Robot Learning from Demonstration with Tactile Signals for Geometry-Dependent Tasks | https://ieeexplore.ieee.org/document/9340818/ | [
"Isabella Huang",
"Ruzena Bajcsy",
"Isabella Huang",
"Ruzena Bajcsy"
] | Deploying robot learning frameworks in unconstrained environments requires robustness and tractability. We must not only equip the robot with a sufficient range of sensing capabilities, but also provide training data in a sample-efficient manner. To this end, we identify and address a need specifically in robot learning from demonstration (LfD) literature to account for not only end-effector pose ... |
Learning Optimized Human Motion via Phase Space Analysis | https://ieeexplore.ieee.org/document/9340773/ | [
"Paul Gesel",
"Francesco Mikulis-Borsoi",
"Dain LaRoche",
"Sajay Arthanat",
"Momotaz Begum",
"Paul Gesel",
"Francesco Mikulis-Borsoi",
"Dain LaRoche",
"Sajay Arthanat",
"Momotaz Begum"
] | This paper proposes a dynamic system based learning from demonstration approach to teach a robot activities of daily living. The approach takes inspiration from human movement literature to formulate trajectory learning as an optimal control problem. We assume a weighted combination of basis objective functions is the true objective function for a demonstrated motion. We derive basis objective fun... |
Tell me what this is: Few-Shot Incremental Object Learning by a Robot | https://ieeexplore.ieee.org/document/9341140/ | [
"Ali Ayub",
"Alan R. Wagner",
"Ali Ayub",
"Alan R. Wagner"
] | For many applications, robots will need to be incrementally trained to recognize the specific objects needed for an application. This paper presents a practical system for incrementally training a robot to recognize different object categories using only a small set of visual examples provided by a human. The paper uses a recently developed state-of-the-art method for few-shot incremental learning... |
Voxel-Based Representation Learning for Place Recognition Based on 3D Point Clouds | https://ieeexplore.ieee.org/document/9340992/ | [
"Sriram Siva",
"Zachary Nahman",
"Hao Zhang",
"Sriram Siva",
"Zachary Nahman",
"Hao Zhang"
] | Place recognition is a critical component towards addressing the key problem of Simultaneous Localization and Mapping (SLAM). Most existing methods use visual images; whereas, place recognition using 3D point clouds, especially based on the voxel representations, has not been well addressed yet. In this paper, we introduce the novel approach of voxel-based representation learning (VBRL) that uses ... |
Robotic Understanding of Spatial Relationships Using Neural-Logic Learning | https://ieeexplore.ieee.org/document/9340917/ | [
"Fujian Yan",
"Dali Wang",
"Hongsheng He",
"Fujian Yan",
"Dali Wang",
"Hongsheng He"
] | Understanding spatial relations of objects is critical in many robotic applications such as grasping, manipulation, and obstacle avoidance. Humans can simply reason object's spatial relations from a glimpse of a scene based on prior knowledge of spatial constraints. The proposed method enables a robot to comprehend spatial relationships among objects from RGB-D data. This paper proposed a neural-l... |
Understanding Contexts Inside Robot and Human Manipulation Tasks through Vision-Language Model and Ontology System in Video Streams | https://ieeexplore.ieee.org/document/9340905/ | [
"Chen Jiang",
"Masood Dehghan",
"Martin Jagersand",
"Chen Jiang",
"Masood Dehghan",
"Martin Jagersand"
] | Manipulation tasks in daily life, such as pouring water, unfold through human intentions. Being able to process contextual knowledge from these Activities of Daily Living (ADLs) over time can help us understand manipulation intentions, which are essential for an intelligent robot to transition smoothly between various manipulation actions. In this paper, to model the intended concepts of manipulat... |
Representing Spatial Object Relations as Parametric Polar Distribution for Scene Manipulation Based on Verbal Commands | https://ieeexplore.ieee.org/document/9340925/ | [
"Rainer Kartmann",
"You Zhou",
"Danqing Liu",
"Fabian Paus",
"Tamim Asfour",
"Rainer Kartmann",
"You Zhou",
"Danqing Liu",
"Fabian Paus",
"Tamim Asfour"
] | Understanding spatial relations is a key element for natural human-robot interaction. Especially, a robot must be able to manipulate a given scene according to a human verbal command specifying desired spatial relations between objects. To endow robots with this ability, a suitable representation of spatial relations is necessary, which should be derivable from human demonstrations. We claim that ... |
Weakly-Supervised Learning for Multimodal Human Activity Recognition in Human-Robot Collaboration Scenarios | https://ieeexplore.ieee.org/document/9340788/ | [
"Clemens Pohlt",
"Thomas Schlegl",
"Sven Wachsmuth",
"Clemens Pohlt",
"Thomas Schlegl",
"Sven Wachsmuth"
] | The ability to synchronize expectations among human-robot teams and understand discrepancies between expectations and reality is essential for human-robot collaboration scenarios. To ensure this, human activities and intentions must be interpreted quickly and reliably by the robot using various modalities. In this paper we propose a multimodal recognition system designed to detect physical interac... |
Tool Shape Optimization through Backpropagation of Neural Network | https://ieeexplore.ieee.org/document/9341583/ | [
"Kento Kawaharazuka",
"Toru Ogawa",
"Cota Nabeshima",
"Kento Kawaharazuka",
"Toru Ogawa",
"Cota Nabeshima"
] | When executing a certain task, human beings can choose or make an appropriate tool to achieve the task. This research especially addresses the optimization of tool shape for robotic tool-use. We propose a method in which a robot obtains an optimized tool shape, tool trajectory, or both, depending on a given task. The feature of our method is that a transition of the task state when the robot moves... |
A Causal Approach to Tool Affordance Learning | https://ieeexplore.ieee.org/document/9341262/ | [
"Jake Brawer",
"Meiying Qin",
"Brian Scassellati",
"Jake Brawer",
"Meiying Qin",
"Brian Scassellati"
] | While abstract knowledge like cause-and-effect relations enables robots to problem-solve in new environments, acquiring such knowledge remains out of reach for many traditional machine learning techniques. In this work, we introduce a method for a robot to learn an explicit model of cause-and-effect by constructing a structural causal model through a mix of observation and self-supervised experime... |
Learning Object Attributes with Category-Free Grounded Language from Deep Featurization | https://ieeexplore.ieee.org/document/9340824/ | [
"Luke E. Richards",
"Kasra Darvish",
"Cynthia Matuszek",
"Luke E. Richards",
"Kasra Darvish",
"Cynthia Matuszek"
] | While grounded language learning, or learning the meaning of language with respect to the physical world in which a robot operates, is a major area in human-robot interaction studies, most research occurs in closed worlds or domain-constrained settings. We present a system in which language is grounded in visual percepts without using categorical constraints by combining CNN-based visual featuriza... |
Visuomotor Mechanical Search: Learning to Retrieve Target Objects in Clutter | https://ieeexplore.ieee.org/document/9341545/ | [
"Andrey Kurenkov",
"Joseph Taglic",
"Rohun Kulkarni",
"Marcus Dominguez-Kuhne",
"Animesh Garg",
"Roberto Martín-Martín",
"Silvio Savarese",
"Andrey Kurenkov",
"Joseph Taglic",
"Rohun Kulkarni",
"Marcus Dominguez-Kuhne",
"Animesh Garg",
"Roberto Martín-Martín",
"Silvio Savarese"
] | When searching for objects in cluttered environments, it is often necessary to perform complex interactions in order to move occluding objects out of the way and fully reveal the object of interest and make it graspable. Due to the complexity of the physics involved and the lack of accurate models of the clutter, planning and controlling precise predefined interactions with accurate outcome is ext... |
Multi-Fingered Active Grasp Learning | https://ieeexplore.ieee.org/document/9340783/ | [
"Qingkai Lu",
"Mark Van der Merwe",
"Tucker Hermans",
"Qingkai Lu",
"Mark Van der Merwe",
"Tucker Hermans"
] | Learning-based approaches to grasp planning are preferred over analytical methods due to their ability to better generalize to new, partially observed objects. However, data collection remains one of the biggest bottlenecks for grasp learning methods, particularly for multi-fingered hands. The relatively high dimensional configuration space of the hands coupled with the diversity of objects common... |
Invisible Marker: Automatic Annotation of Segmentation Masks for Object Manipulation | https://ieeexplore.ieee.org/document/9341332/ | [
"Kuniyuki Takahashi",
"Kenta Yonekura",
"Kuniyuki Takahashi",
"Kenta Yonekura"
] | We propose a method to annotate segmentation masks accurately and automatically using invisible marker for object manipulation. Invisible marker is invisible under visible (regular) light conditions, but becomes visible under invisible light, such as ultraviolet (UV) light. By painting objects with the invisible marker, and by capturing images while alternately switching between regular and UV lig... |
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation | https://ieeexplore.ieee.org/document/9341282/ | [
"Yu Liu",
"Lingqiao Liu",
"Haokui Zhang",
"Hamid Rezatofighi",
"Qingsen Yan",
"Ian Reid",
"Yu Liu",
"Lingqiao Liu",
"Haokui Zhang",
"Hamid Rezatofighi",
"Qingsen Yan",
"Ian Reid"
] | Video object segmentation plays a vital role to many robotic tasks, beyond the satisfied accuracy, quickly adapt to the new scenario with very limited annotations and conduct a quick inference are also important. In this paper, we are specifically concerned with the task of fast segmenting all pixels of a target object in all frames, given the annotation mask in the first frame. Even when such ann... |
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation | https://ieeexplore.ieee.org/document/9341531/ | [
"Mingmei Cheng",
"Le Hui",
"Jin Xie",
"Jian Yang",
"Hui Kong",
"Mingmei Cheng",
"Le Hui",
"Jin Xie",
"Jian Yang",
"Hui Kong"
] | In this paper, we propose a cascaded non-local neural network for point cloud segmentation. The proposed network aims to build the long-range dependencies of point clouds for the accurate segmentation. Specifically, we develop a novel cascaded non-local module, which consists of the neighborhood-level, superpoint-level and global-level non-local blocks. First, in the neighborhood-level block, we e... |
Robust and Efficient Object Change Detection by Combining Global Semantic Information and Local Geometric Verification | https://ieeexplore.ieee.org/document/9341664/ | [
"Edith Langer",
"Timothy Patten",
"Markus Vincze",
"Edith Langer",
"Timothy Patten",
"Markus Vincze"
] | Identifying new, moved or missing objects is an important capability for robot tasks such as surveillance or maintaining order in homes, offices and industrial settings. However, current approaches do not distinguish between novel objects or simple scene readjustments nor do they sufficiently deal with localization error and sensor noise. To overcome these limitations, we combine the strengths of ... |
HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images | https://ieeexplore.ieee.org/document/9341192/ | [
"Johan Vertens",
"Jannik Zürn",
"Wolfram Burgard",
"Johan Vertens",
"Jannik Zürn",
"Wolfram Burgard"
] | The majority of learning-based semantic segmentation methods are optimized for daytime scenarios and favorable lighting conditions. Real-world driving scenarios, however, entail adverse environmental conditions such as nighttime illumination or glare which remain a challenge for existing approaches. In this work, we propose a multimodal semantic segmentation model that can be applied during daytim... |
PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation | https://ieeexplore.ieee.org/document/9341776/ | [
"JuYoung Yang",
"Chanho Lee",
"Pyunghwan Ahn",
"Haeil Lee",
"Eojindl Yi",
"Junmo Kim",
"JuYoung Yang",
"Chanho Lee",
"Pyunghwan Ahn",
"Haeil Lee",
"Eojindl Yi",
"Junmo Kim"
] | Following considerable development in 3D scanning technologies, many studies have recently been proposed with various approaches for 3D vision tasks, including some methods that utilize 2D convolutional neural networks (CNNs). However, even though 2D CNNs have achieved high performance in many 2D vision tasks, existing works have not effectively applied them onto 3D vision tasks. In particular, se... |
Single-Shot Panoptic Segmentation | https://ieeexplore.ieee.org/document/9341546/ | [
"Mark Weber",
"Jonathon Luiten",
"Bastian Leibe",
"Mark Weber",
"Jonathon Luiten",
"Bastian Leibe"
] | We present a novel end-to-end single-shot method that segments countable object instances (things) as well as background regions (stuff) into a non-overlapping panoptic segmentation at almost video frame rate. Current state-of-the-art methods are far from reaching video frame rate and mostly rely on merging instance segmentation with semantic background segmentation, making them impractical to use... |
Meta-Learning Deep Visual Words for Fast Video Object Segmentation | https://ieeexplore.ieee.org/document/9341737/ | [
"Harkirat Singh Behl",
"Mohammad Naja",
"Anurag Arnab",
"Philip H.S. Torr",
"Harkirat Singh Behl",
"Mohammad Naja",
"Anurag Arnab",
"Philip H.S. Torr"
] | Personal robots and driverless cars need to be able to operate in novel environments and thus quickly and efficiently learn to recognise new object classes. We address this problem by considering the task of video object segmentation. Previous accurate methods for this task finetune a model using the first annotated frame, and/or use additional inputs such as optical flow and complex post-processi... |
Fully Convolutional Geometric Features for Category-level Object Alignment | https://ieeexplore.ieee.org/document/9341550/ | [
"Qiaojun Feng",
"Nikolay Atanasov",
"Qiaojun Feng",
"Nikolay Atanasov"
] | This paper focuses on pose registration of different object instances from the same category. This is required in online object mapping because object instances detected at test time usually differ from the training instances. Our approach transforms instances of the same category to a normalized canonical coordinate frame and uses metric learning to train fully convolutional geometric features. T... |
Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks | https://ieeexplore.ieee.org/document/9340816/ | [
"Daniil Pakhomov",
"Wei Shen",
"Nassir Navab",
"Daniil Pakhomov",
"Wei Shen",
"Nassir Navab"
] | Surgical tool segmentation in endoscopic images is an important problem: it is a crucial step towards full instrument pose estimation and it is used for integration of pre- and intra-operative images into the endoscopic view. While many recent approaches based on convolutional neural networks have shown great results, a key barrier to progress lies in the acquisition of a large number of manually-... |
LiDAR Panoptic Segmentation for Autonomous Driving | https://ieeexplore.ieee.org/document/9340837/ | [
"Andres Milioto",
"Jens Behley",
"Chris McCool",
"Cyrill Stachniss",
"Andres Milioto",
"Jens Behley",
"Chris McCool",
"Cyrill Stachniss"
] | Truly autonomous driving without the need for human intervention can only be attained when self-driving cars fully understand their surroundings. Most of these vehicles rely on a suite of active and passive sensors. LiDAR sensors are a cornerstone in most of these hardware stacks, and leveraging them as a complement to other passive sensors such as RGB cameras is an enticing goal. Understanding th... |
LiDAR guided Small obstacle Segmentation | https://ieeexplore.ieee.org/document/9341465/ | [
"Aasheesh Singh",
"Aditya Kamireddypalli",
"Vineet Gandhi",
"K Madhava Krishna",
"Aasheesh Singh",
"Aditya Kamireddypalli",
"Vineet Gandhi",
"K Madhava Krishna"
] | Detecting small obstacles on the road is critical for autonomous driving. In this paper, we present a method to reliably detect such obstacles through a multi-modal framework of sparse LiDAR(VLP-16) and Monocular vision. LiDAR is employed to provide additional context in the form of confidence maps to monocular segmentation networks. We show significant performance gains when the context is fed as... |
Localizing Against Drawn Maps via Spline-Based Registration | https://ieeexplore.ieee.org/document/9341630/ | [
"Kevin Chen",
"Marynel Vázquez",
"Silvio Savarese",
"Kevin Chen",
"Marynel Vázquez",
"Silvio Savarese"
] | We propose a method to facilitate robot navigation relative to sketched maps of human environments. Our main contribution centers around using thin plate splines for registering the robot's LIDAR observation with the hand-drawn maps. Thin plate splines are particularly effective for this task because they are able to handle many of the nonrigid deformations commonly seen in sketches of maps, which... |
KR-Net: A Dependable Visual Kidnap Recovery Network for Indoor Spaces | https://ieeexplore.ieee.org/document/9341597/ | [
"Janghun Hyeon",
"Dongwoo Kim",
"Bumchul Jang",
"Hyunga Choi",
"Dong Hoon Yi",
"Kyungho Yoo",
"Jeongae Choi",
"Nakju Doh",
"Janghun Hyeon",
"Dongwoo Kim",
"Bumchul Jang",
"Hyunga Choi",
"Dong Hoon Yi",
"Kyungho Yoo",
"Jeongae Choi",
"Nakju Doh"
] | In this paper, we propose a dependable visual kidnap recovery (KR) framework that pinpoints a unique pose in a given 3D map when a device is turned on. For this framework, we first develop indoor-GeM (i-GeM), which is an extension of GeM [1] but considerably more robust than other global descriptors [2]-[4], including GeM itself. Then, we propose a convolutional neural network (CNN)-based system c... |
Mobile Robot Localization under Non-Gaussian noise using Correntropy Similarity Metric | https://ieeexplore.ieee.org/document/9340795/ | [
"Elerson R. S. Santos",
"Marcos A. M. Vieira",
"Gaurav S. Sukhatme",
"Elerson R. S. Santos",
"Marcos A. M. Vieira",
"Gaurav S. Sukhatme"
] | In this paper, we study the localization problem under non-Gaussian noise. In particular, we consider systems that can be represented by a state transition and a measurement component. The state transition indicates how the system evolves given a control variable. The measurement component compares, for a given state, the received and predicted measurements. Here we consider a radio based range se... |
SpoxelNet: Spherical Voxel-based Deep Place Recognition for 3D Point Clouds of Crowded Indoor Spaces | https://ieeexplore.ieee.org/document/9341549/ | [
"Min Young Chang",
"Suyong Yeon",
"Soohyun Ryu",
"Donghwan Lee",
"Min Young Chang",
"Suyong Yeon",
"Soohyun Ryu",
"Donghwan Lee"
] | With its essential role in achieving full autonomy of robot navigation, place recognition has been widely studied with various approaches. Recently, numerous point cloud-based methods with deep learning implementation have been proposed with promising results for their application in outdoor environments. However, their performances are not as promising in indoor spaces because of the high level o... |
Online Localization with Imprecise Floor Space Maps using Stochastic Gradient Descent | https://ieeexplore.ieee.org/document/9340793/ | [
"Zhikai Li",
"Marcelo H. Ang",
"Daniela Rus",
"Zhikai Li",
"Marcelo H. Ang",
"Daniela Rus"
] | Many indoor spaces have constantly changing layouts and may not be mapped by an autonomous vehicle, yet maps such as floor plans or evacuation maps of these places are common. We propose a method for an autonomous robot to localize itself on such maps with inconsistent scale using Stochastic Gradient Descent (SGD) with scan matching using a 2D LiDAR. We also introduce a new scale state in 2D local... |
BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane | https://ieeexplore.ieee.org/document/9341151/ | [
"Riku Murai",
"Sajad Saeedi",
"Paul H. J. Kelly",
"Riku Murai",
"Sajad Saeedi",
"Paul H. J. Kelly"
] | Focal-plane Sensor-processor (FPSP) is a next-generation camera technology which enables every pixel on the sensor chip to perform computation in parallel, on the focal plane where the light intensity is captured. SCAMP-5 is a general-purpose FPSP used in this work and it carries out computations in the analog domain before analog to digital conversion. By extracting features from the image on the... |
Utilizing Sacrificial Molding for Embedding Motion Controlling Endostructures in Soft Pneumatic Actuators | https://ieeexplore.ieee.org/document/9341280/ | [
"Ajinkya Bhat",
"Raye Chen-Hua Yeow",
"Ajinkya Bhat",
"Raye Chen-Hua Yeow"
] | The field of soft robotics has evolved as a domain for developing light, compliant and safe actuators. However, one of the challenges in the field is the lack of repeatable fabrication techniques as well as customizability that restricts the application of soft robots. We present a fabrication technique using sacrificial molding to fabricate pneumatic channels that are repeatable and less prone to... |
Simultaneous position-stiffness control of antagonistically driven twisted-coiled polymer actuators using model predictive control | https://ieeexplore.ieee.org/document/9340727/ | [
"Tuan Luong",
"Kihyeon Kim",
"Sungwon Seo",
"Jeongmin Jeon",
"Ja Choon Koo",
"Hyouk Ryeol Choi",
"Hyungpil Moon",
"Tuan Luong",
"Kihyeon Kim",
"Sungwon Seo",
"Jeongmin Jeon",
"Ja Choon Koo",
"Hyouk Ryeol Choi",
"Hyungpil Moon"
] | Super-coiled polymer (SCP) artificial muscles have many interesting properties that show potentials for making high performance bionic devices. To realize human-like robotic devices from this type of actuator, it is important for the SCP driven mechanisms to achieve human-like performance, such as compliant behaviors through antagonistic mechanisms. This paper presents the simultaneous position-st... |
Towards Gradient-Based Actuation of Magnetic Soft Robots Using a Six-Coil Electromagnetic System | https://ieeexplore.ieee.org/document/9341172/ | [
"Venkatasubramanian Kalpathy Venkiteswaran",
"Sarthak Misra",
"Venkatasubramanian Kalpathy Venkiteswaran",
"Sarthak Misra"
] | Soft materials with embedded magnetic properties can be actuated in a contactless manner for dexterous motion in restricted and unstructured environments. Magnetic soft robots have been demonstrated to be capable of versatile and programmable untethered motion. However, magnetic soft robots reported in literature are typically actuated by utilizing magnetic fields to generate torques that produce ... |
Model Identification of a Soft Robotic Neck | https://ieeexplore.ieee.org/document/9341779/ | [
"Fernando Quevedo",
"Jorge Muñoz Yañez-Barnuevo",
"Juan A. Castano",
"Concepción A. Monje",
"Carlos Balaguer",
"Fernando Quevedo",
"Jorge Muñoz Yañez-Barnuevo",
"Juan A. Castano",
"Concepción A. Monje",
"Carlos Balaguer"
] | Soft links and actuators are nowadays emerging technologies aiming to overcome some problems in robotics such as weight, cost or human interaction. However, the nonlinear nature of their elements can make their characterization challenging and hinder the use of standard control engineering tools. In this paper, we explore different state-of-the-art identification methods for the soft neck, in orde... |
Observer-based Control of Inflatable Robot with Variable Stiffness | https://ieeexplore.ieee.org/document/9341785/ | [
"Ahmad Ataka",
"Taqi Abrar",
"Fabrizio Putzu",
"Hareesh Godaba",
"Kaspar Althoefer",
"Ahmad Ataka",
"Taqi Abrar",
"Fabrizio Putzu",
"Hareesh Godaba",
"Kaspar Althoefer"
] | In the last decade, soft robots have been at the forefront of a robotic revolution. Due to the flexibility of the soft materials employed, soft robots are equipped with a capability to execute new tasks in new application areas -beyond what can be achieved using classical rigid-link robots. Despite these promising properties, many soft robots nowadays lack the capability to exert sufficient force ... |
Solving Cosserat Rod Models via Collocation and the Magnus Expansion | https://ieeexplore.ieee.org/document/9340827/ | [
"Andrew L. Orekhov",
"Nabil Simaan",
"Andrew L. Orekhov",
"Nabil Simaan"
] | Choosing a kinematic model for a continuum robot typically involves making a tradeoff between accuracy and computational complexity. One common modeling approach is to use the Cosserat rod equations, which have been shown to be accurate for many types of continuum robots. This approach, however, still presents significant computational cost, particularly when many Cosserat rods are coupled via kin... |
Design of Fully Soft Actuator with Double-Helix Tendon Routing Path for Twisting Motion | https://ieeexplore.ieee.org/document/9341363/ | [
"Joonmyeong Choi",
"Se Hyeok Ahn",
"Kyu-Jin Cho",
"Joonmyeong Choi",
"Se Hyeok Ahn",
"Kyu-Jin Cho"
] | Soft actuators have been widely studied in recent years because of their ability to adapt to diverse environments and safely interact with humans. Their softness broadens their potential range of medical applications since they can provide inherent safety. Among the various motions a soft robot can perform, "torsion" can maximize the efficiency of motion in confined spaces like the human abdominal... |
Design of a Highly-Maneuverable Pneumatic Soft Actuator Driven by Intrinsic SMA Coils (PneuSMA Actuator) | https://ieeexplore.ieee.org/document/9340803/ | [
"Emily A. Allen",
"John P. Swensen",
"Emily A. Allen",
"John P. Swensen"
] | This paper presents the design of a new soft pneumatic actuator whose direction and magnitude of bending may be precisely controlled via activation of different shape memory alloy (SMA) springs within the actuator, in conjunction with pneumatic actuation. This design is inspired by examples seen in nature such as the human tongue, where the combination of hydrostatic pressure and contraction of in... |
Multi-Modal Pneumatic Actuator for Twisting, Extension, and Bending | https://ieeexplore.ieee.org/document/9341555/ | [
"Roman Balak",
"Yi Chen Mazumdar",
"Roman Balak",
"Yi Chen Mazumdar"
] | Soft pneumatic actuators are commonly used in robotics for creating single-axis compression, extension, or bending motions. If these actuators are composed of compliant materials, they can also have low off-axis stiffnesses, making it difficult to restrict off-axis motions. In this work, we exploit the low off-axis stiffnesses of pneumatic actuators to design a modular actuator system that is capa... |
The Multi-material Actuator for Variable Stiffness (MAVS): Design, Modeling, and Characterization of a Soft Actuator for Lateral Ankle Support | https://ieeexplore.ieee.org/document/9341430/ | [
"Carly M. Thalman",
"Tiffany Hertzell",
"Marielle Debeurre",
"Hyunglae Lee",
"Carly M. Thalman",
"Tiffany Hertzell",
"Marielle Debeurre",
"Hyunglae Lee"
] | This paper presents the design of the Multi-material Actuator for Variable Stiffness (MAVS), which consists of an inflatable soft fabric actuator fixed between two layers of rigid retainer pieces. The MAVS is designed to be integrated with a soft robotic ankle-foot orthosis (SR-AFO) exosuit to aid in supporting the human ankle in the inversion/eversion directions. This design aims to assist indivi... |
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