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Magnetically-Connected Modular Reconfigurable Mini-robotic System with Bilateral Isokinematic Mapping and Fast On-site Assembly towards Minimally Invasive Procedures | https://ieeexplore.ieee.org/document/9561141/ | [
"Xiao Xiao",
"Shilei Xu",
"Changsheng Li",
"Xiaoyi Gu",
"Huxin Gao",
"Max Q.-H. Meng",
"Hongliang Ren",
"Xiao Xiao",
"Shilei Xu",
"Changsheng Li",
"Xiaoyi Gu",
"Huxin Gao",
"Max Q.-H. Meng",
"Hongliang Ren"
] | This paper presents a modular and reconfigurable mini-robotic system with 5 degrees of freedom (DoFs) towards minimally invasive surgery (MIS). The mini-robotic system consists of two modules, a 2-DoFs rotational end-effector, and a 3-DoFs positioning platform. The 2-DoFs rotational end-effector is based on a spring-spherical joint mechanism, whose rotation is controlled by Bowden-cable. The 3-DoF... |
Reinforcement Learning Control of A Novel Magnetic Actuated Flexible-joint Robotic Camera System for Single Incision Laparoscopic Surgery | https://ieeexplore.ieee.org/document/9560927/ | [
"Dong Xu",
"Yuanlin Zhang",
"Wenshuai Tan",
"Hongxing Wei",
"Dong Xu",
"Yuanlin Zhang",
"Wenshuai Tan",
"Hongxing Wei"
] | This paper describes the control of a novel Magnetic Actuated Flexible-joint Robotic Surgical (MAFRS) camera system with four degrees of freedom (4-DOF) for single incision laparoscopic surgery. Based on the idea of motion decoupling, we designed a novel MAFRS system which is consists of an external driving device and a motor-free insertable wireless robotic device with a hollow flexible joint. Du... |
Muscular stimulation based biological actuator from locust’s hindleg | https://ieeexplore.ieee.org/document/9560875/ | [
"Songsong Ma",
"Peng Liu",
"Shen Liu",
"Yao Li",
"Bing Li",
"Songsong Ma",
"Peng Liu",
"Shen Liu",
"Yao Li",
"Bing Li"
] | The development and control of biological actuators have been an active research field. Biological actuators revealed high mobility with compact dimensions, which is critical for the design of microrobots. The powerful kicking motion of the locust is important for its quick jumping. Herein, we examined the kicking process of the locust’s hindleg and controlled the flexion and extension motions via... |
An Efficient Parallel Self-assembly Planning Algorithm for Modular Robots in Environments with Obstacles | https://ieeexplore.ieee.org/document/9560863/ | [
"Lianxin Zhang",
"Zhang-Hua Fu",
"Hengli Liu",
"Qingquan Liu",
"Xiaoqiang Ji",
"Huihuan Qian",
"Lianxin Zhang",
"Zhang-Hua Fu",
"Hengli Liu",
"Qingquan Liu",
"Xiaoqiang Ji",
"Huihuan Qian"
] | Self-assembly has attracted growing interests in modular robotics during past decades. Recent work accelerates the assembly process by parallelizing the docking actions among robots. However, these methods can only apply to ideal environments without obstacles. Otherwise, robots will get trapped during the assembly process, due to the complex scenes with obstacles. This paper presents an efficient... |
Multi-robot Informative Path Planning using a Leader-Follower Architecture | https://ieeexplore.ieee.org/document/9561955/ | [
"Gianni A. Di Caro",
"Abdul Wahab Ziaullah Yousaf",
"Gianni A. Di Caro",
"Abdul Wahab Ziaullah Yousaf"
] | We consider typical scenarios where an autonomous multi-robot team is used for surveying a large region. The desired output is a spatial map of the physical values of interest. Accounting for spatial correlation and uncertainty, the map is modeled using a Gaussian Process. Considering real-world constraints such as limited time budget and collision avoidance, we model team’s mission as a joint inf... |
Tightly-Coupled Perception and Navigation of Heterogeneous Land-Air Robots in Complex Scenarios | https://ieeexplore.ieee.org/document/9562042/ | [
"Yufeng Yue",
"Mingxing Wen",
"Yosmar Putra",
"Meiling Wang",
"Danwei Wang",
"Yufeng Yue",
"Mingxing Wen",
"Yosmar Putra",
"Meiling Wang",
"Danwei Wang"
] | In unstructured and unknown environments, heterogeneous robots must be able to perceive the environment, coordinate with each other and complete tasks collaboratively with onboard sensors. In this paper, a tightly-coupled perception and navigation framework is proposed for heterogeneous land-air robots, which forms a closed loop of perception-navigation for heterogeneous robots. The key novelty of... |
Proactive Action Visual Residual Reinforcement Learning for Contact-Rich Tasks Using a Torque-Controlled Robot | https://ieeexplore.ieee.org/document/9561162/ | [
"Yunlei Shi",
"Zhaopeng Chen",
"Hongxu Liu",
"Sebastian Riedel",
"Chunhui Gao",
"Qian Feng",
"Jun Deng",
"Jianwei Zhang",
"Yunlei Shi",
"Zhaopeng Chen",
"Hongxu Liu",
"Sebastian Riedel",
"Chunhui Gao",
"Qian Feng",
"Jun Deng",
"Jianwei Zhang"
] | Contact-rich manipulation tasks are commonly found in modern manufacturing settings. However, manually designing a robot controller is considered hard for traditional control methods as the controller requires an effective combination of modalities and vastly different characteristics. In this paper, we first consider incorporating operational space visual and haptic information into a reinforceme... |
ParametricNet: 6DoF Pose Estimation Network for Parametric Shapes in Stacked Scenarios | https://ieeexplore.ieee.org/document/9561181/ | [
"Long Zeng",
"Wei Jie Lv",
"Xin Yu Zhang",
"Yong Jin Liu",
"Long Zeng",
"Wei Jie Lv",
"Xin Yu Zhang",
"Yong Jin Liu"
] | Most industrial parts are parametric and their special properties are not fully explored yet. This paper proposes a new 6DoF pose estimation network for parametric shapes in stacked scenarios (ParametricNet). It treats a parametric shape, instead of a part object, as a category. The keypoints of individual instances are learned with point- wise regression and Hough voting scheme, from which specif... |
Optimal Online Dispatch for High-Capacity Shared Autonomous Mobility-on-Demand Systems | https://ieeexplore.ieee.org/document/9561281/ | [
"Cheng Li",
"David Parker",
"Qi Hao",
"Cheng Li",
"David Parker",
"Qi Hao"
] | Shared autonomous mobility-on-demand systems hold great promise for improving the efficiency of urban transportation, but are challenging to implement due to the huge scheduling search space and highly dynamic nature of requests. This paper presents a novel optimal schedule pool (OSP) assignment approach to optimally dispatch high-capacity ride-sharing vehicles in real time, including: (1) an incr... |
An Improved Magnetic Spot Navigation for Replacing the Barcode Navigation in Automated Guided Vehicles | https://ieeexplore.ieee.org/document/9561316/ | [
"Houde Dai",
"Pengfei Guo",
"Hongyu Chen",
"Silin Zhao",
"Penghua Liu",
"Guijuan Lin",
"Houde Dai",
"Pengfei Guo",
"Hongyu Chen",
"Silin Zhao",
"Penghua Liu",
"Guijuan Lin"
] | The barcode navigation based on QR (quick response) codes is widely employed in industrial logistics due to its accurate localization and flexible movement paths. However, the regular repair of damaged barcodes and robot speed control when approaching the barcodes are required. In this study, we presented an improved magnetic spot navigation approach to replace the barcode navigation for automated... |
ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking | https://ieeexplore.ieee.org/document/9561564/ | [
"Bowen Li",
"Changhong Fu",
"Fangqiang Ding",
"Junjie Ye",
"Fuling Lin",
"Bowen Li",
"Changhong Fu",
"Fangqiang Ding",
"Junjie Ye",
"Fuling Lin"
] | Prior correlation filter (CF)-based tracking methods for unmanned aerial vehicles (UAVs) have virtually focused on tracking in the daytime. However, when the night falls, the trackers will encounter more harsh scenes, which can easily lead to tracking failure. In this regard, this work proposes a novel tracker with anti-dark function (ADTrack). The proposed method integrates an efficient and effec... |
Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label | https://ieeexplore.ieee.org/document/9561931/ | [
"Guangze Zheng",
"Changhong Fu",
"Junjie Ye",
"Fuling Lin",
"Fangqiang Ding",
"Guangze Zheng",
"Changhong Fu",
"Junjie Ye",
"Fuling Lin",
"Fangqiang Ding"
] | Unmanned aerial vehicle (UAV) based visual tracking has been confronted with numerous challenges, e.g., object motion and occlusion. These challenges generally introduce unexpected mutations of target appearance and result in tracking failure. However, prevalent discriminative correlation filter (DCF) based trackers are insensitive to target mutations due to a predefined label, which concentrates ... |
Siamese Anchor Proposal Network for High-Speed Aerial Tracking | https://ieeexplore.ieee.org/document/9560756/ | [
"Changhong Fu",
"Ziang Cao",
"Yiming Li",
"Junjie Ye",
"Chen Feng",
"Changhong Fu",
"Ziang Cao",
"Yiming Li",
"Junjie Ye",
"Chen Feng"
] | In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency. Therefore, their real-world deployment on mobile platforms like the unmanned aerial vehicle (UAV) is impeded. In this work, a novel two-stage Siamese network-based method is proposed for aerial tracking, i.e., stage-1 for high-quality anchor proposal generation, stage-2 for refi... |
Modeling Affect-based Intrinsic Rewards for Exploration and Learning | https://ieeexplore.ieee.org/document/9562098/ | [
"Dean Zadok",
"Daniel McDuff",
"Ashish Kapoor",
"Dean Zadok",
"Daniel McDuff",
"Ashish Kapoor"
] | Positive affect has been linked to increased interest, curiosity and satisfaction in human learning. In reinforcement learning, extrinsic rewards are often sparse and difficult to define, intrinsically motivated learning can help address these challenges. We argue that positive affect is an important intrinsic reward that effectively helps drive exploration that is useful in gathering experiences.... |
A Multi-Level Network for Human Pose Estimation | https://ieeexplore.ieee.org/document/9560980/ | [
"Zhanpeng Shao",
"Peng Liu",
"Youfu Li",
"Jianyu Yang",
"Xiaolong Zhou",
"Zhanpeng Shao",
"Peng Liu",
"Youfu Li",
"Jianyu Yang",
"Xiaolong Zhou"
] | Although multi-person human pose estimation has made great progress in recent years, the challenges such as various scales of persons, occluded keypoints, and crowded backgrounds in complex scenes are still remained to be solved. In this paper, we propose a novel multi-level pose estimation network (MLPE) to learn multi-level features that can preserve both the strong semantic clues and spatial re... |
Open-set Intersection Intention Prediction for Autonomous Driving | https://ieeexplore.ieee.org/document/9561660/ | [
"Fei Li",
"Xiangxu Li",
"Jun Luo",
"Shiwei Fan",
"Hongbo Zhang",
"Fei Li",
"Xiangxu Li",
"Jun Luo",
"Shiwei Fan",
"Hongbo Zhang"
] | Intention prediction is a crucial task for Autonomous Driving (AD). Due to the variety of size and layout of intersections, it is challenging to predict intention of human driver at different intersections, especially unseen and irregular intersections. In this paper, we formulate the prediction of intention at intersections as an open-set prediction problem that requires context specific matching... |
A general elimination strategy for camera motion estimation | https://ieeexplore.ieee.org/document/9561300/ | [
"Yaqing Ding",
"Yingna Su",
"Chengzhong Xu",
"Jian Yang",
"Hui Kong",
"Yaqing Ding",
"Yingna Su",
"Chengzhong Xu",
"Jian Yang",
"Hui Kong"
] | Camera motion estimation, such as relative pose estimation and absolute pose estimation, are fundamental problems in computer vision and robotics. To obtain the motion parameters, classical methods rely on studying the properties of the geometric matrices, e.g., rotation matrix, essential matrix, homography matrix. The well known five-point algorithm was successfully derived using the singular con... |
Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG | https://ieeexplore.ieee.org/document/9560928/ | [
"Chen-Chen Fan",
"Haiqun Xie",
"Liang Peng",
"Hongjun Yang",
"Zhen-Liang Ni",
"Guan’an Wang",
"Yan-Jie Zhou",
"Sheng Chen",
"Zhijie Fang",
"Shuyun Huang",
"Zeng-Guang Hou",
"Chen-Chen Fan",
"Haiqun Xie",
"Liang Peng",
"Hongjun Yang",
"Zhen-Liang Ni",
"Guan’an Wang",
"Yan-Jie Zhou",
"Sheng Chen",
"Zhijie Fang",
"Shuyun Huang",
"Zeng-Guang Hou"
] | Medical diagnostic robot systems have been paid more and more attention due to its objectivity and accuracy. The diagnosis of mild cognitive impairment (MCI) is considered an effective means to prevent Alzheimer's disease (AD). Doctors diagnose MCI based on various clinical examinations, which are expensive and the diagnosis results rely on the knowledge of doctors. Therefore, it is necessary to d... |
Line-based Automatic Extrinsic Calibration of LiDAR and Camera | https://ieeexplore.ieee.org/document/9561216/ | [
"Xinyu Zhang",
"Shifan Zhu",
"Shichun Guo",
"Jun Li",
"Huaping Liu",
"Xinyu Zhang",
"Shifan Zhu",
"Shichun Guo",
"Jun Li",
"Huaping Liu"
] | Reliable real-time extrinsic parameters of 3D Light Detection and Ranging (LiDAR) and camera are a key component of multi-modal perception systems. However, extrinsic transformation may drift gradually during operation, which can result in decreased accuracy of perception system. To solve this problem, we propose a line-based method that enables automatic online extrinsic calibration of LiDAR and ... |
RIL: Riemannian Incremental Learning of the Inertial Properties of the Robot Body Schema | https://ieeexplore.ieee.org/document/9561425/ | [
"Fernando Díaz Ledezma",
"Sami Haddadin",
"Fernando Díaz Ledezma",
"Sami Haddadin"
] | We transform classical robot inertial parameter identification into an online learning problem by integrating state-of-the-art gradient descent techniques and first-order principles from mechanics and differential geometry. Through this, incremental learning of fully physically feasible inertial properties without requiring any prior information is made possible. This is achieved using a version o... |
Two-stream 2D/3D Residual Networks for Learning Robot Manipulations from Human Demonstration Videos | https://ieeexplore.ieee.org/document/9561308/ | [
"Xin Xu",
"Kun Qian",
"Bo Zhou",
"Shenghao Chen",
"Yitong Li",
"Xin Xu",
"Kun Qian",
"Bo Zhou",
"Shenghao Chen",
"Yitong Li"
] | Learning manipulation skills from observing human demonstration videos is a promising aspect for intelligent robotic systems. Recent advances in video to command provide an end-to-end approach to translate a video into robot plans. However, the general video captioning methods focus more on the understanding of the full frame, while they lack the consideration of the spatio-temporal features in vi... |
Waypoints updating based on Adam and ILC for path learning in physical human-robot interaction | https://ieeexplore.ieee.org/document/9561197/ | [
"Jingkang Xia",
"Chenjian Song",
"Deqing Huang",
"Xueyan Xing",
"Lei Ma",
"Yanan Li",
"Jingkang Xia",
"Chenjian Song",
"Deqing Huang",
"Xueyan Xing",
"Lei Ma",
"Yanan Li"
] | This paper presents a novel method for learning and tracking of the desired path of the human partner in physical human-robot interaction. Combining the Adam optimization algorithm with iteration learning control (ILC), a path learning method is designed to generate and update reference waypoints according to the human partner’s desired path. This method firstly uses the Adam optimization algorith... |
A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video | https://ieeexplore.ieee.org/document/9561605/ | [
"Junfa Liu",
"Juan Rojas",
"Yihui Li",
"Zhijun Liang",
"Yisheng Guan",
"Ning Xi",
"Haifei Zhu",
"Junfa Liu",
"Juan Rojas",
"Yihui Li",
"Zhijun Liang",
"Yisheng Guan",
"Ning Xi",
"Haifei Zhu"
] | Spatio-temporal information is key to resolve occlusion and depth ambiguity in 3D human pose estimation. Previous methods have focused on either temporal contexts or local-to-global architectures that embed fixed-length spatiotemporal information. To date, there have not been effective proposals to simultaneously and flexibly capture varying spatiotemporal sequences and effectively achieves real-t... |
Micro Robotic Manipulation System for the Force Stimulation of Muscle Fiber-like Cell Structure | https://ieeexplore.ieee.org/document/9560846/ | [
"Xie Chen",
"Qing Shi",
"Shingo Shimoda",
"Tao Sun",
"Huaping Wang",
"Qiang Huang",
"Toshio Fukuda",
"Xie Chen",
"Qing Shi",
"Shingo Shimoda",
"Tao Sun",
"Huaping Wang",
"Qiang Huang",
"Toshio Fukuda"
] | Many previous works have facilitated muscle cell (C2C12) alignment to form fiber-like cell structures. However, there still remains a challenge how to induce C2C12 myoblasts in the cell structures to differentiate into matured myocytes to form a functional muscle tissue, while external mechanical stimulation has been proved to have good effects on proliferation and differentiation of myoblasts. In... |
A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics | https://ieeexplore.ieee.org/document/9561911/ | [
"Tian Liu",
"Xuelong Sun",
"Cheng Hu",
"Qinbing Fu",
"Shigang Yue",
"Tian Liu",
"Xuelong Sun",
"Cheng Hu",
"Qinbing Fu",
"Shigang Yue"
] | This paper describes a versatile platform for swarm robotics research. It integrates multiple pheromone communication with a dynamic visual scene along with real time data transmission and localization of multiple-robots. The platform has been built for inquiries into social insect behavior and bio-robotics. By introducing a new research scheme to coordinate olfactory and visual cues, it not only ... |
3D Periodic Magnetic Servoing System for Microrobot Actuation Using Decoupled Asynchronous Repetitive Control Approach | https://ieeexplore.ieee.org/document/9560870/ | [
"Zhiyong Sun",
"Yu Cheng",
"Chao Zhou",
"Erkang Cheng",
"Gengliang Chen",
"Lixin Dong",
"Bo Song",
"Zhiyong Sun",
"Yu Cheng",
"Chao Zhou",
"Erkang Cheng",
"Gengliang Chen",
"Lixin Dong",
"Bo Song"
] | To date, untethered microrobots have been receiving tremendous attention for playing implacable roles of maneuverable tools in fields such as microfabrication and biomanipulation. Typical actuation of such untethered tiny robots is the magnetic field-based approaches, including gradient and rotational methods. Compared to the gradient type method, the rotational approach requires much less magneti... |
Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Model | https://ieeexplore.ieee.org/document/9561472/ | [
"Zhaoting Li",
"Jiankun Wang",
"Max Q.-H. Meng",
"Zhaoting Li",
"Jiankun Wang",
"Max Q.-H. Meng"
] | Robot path planning is difficult to solve due to the contradiction between the optimality of results and the complexity of algorithms, even in 2D environments. To find an optimal path, the algorithm needs to search all the state space, which costs many computation resources. To address this issue, we present a novel recurrent generative model (RGM), which generates efficient heuristic to reduce th... |
Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas | https://ieeexplore.ieee.org/document/9561550/ | [
"Leighton Collins",
"Payam Ghassemi",
"Ehsan T. Esfahani",
"David Doermann",
"Karthik Dantu",
"Souma Chowdhury",
"Leighton Collins",
"Payam Ghassemi",
"Ehsan T. Esfahani",
"David Doermann",
"Karthik Dantu",
"Souma Chowdhury"
] | This paper presents a novel multi-robot coverage path planning (CPP) algorithm - aka SCoPP - that provides a time-efficient solution, with workload balanced plans for each robot in a multi-robot system, based on their initial states. This algorithm accounts for discontinuities (e.g., no-fly zones) in a specified area of interest, and provides an optimized ordered list of way-points per robot using... |
Time and Energy Optimized Trajectory Generation for Multi-Agent Constellation Changes | https://ieeexplore.ieee.org/document/9561702/ | [
"Paul Ladinig",
"Bernhard Rinner",
"Stephan Weiss",
"Paul Ladinig",
"Bernhard Rinner",
"Stephan Weiss"
] | Planning the simultaneous movement of multiple agents represents a challenging coordination problem, and ideally safety and efficiency are jointly addressed. This paper introduces a planning algorithm for fast and energy-efficient trajectories with reduced collision potential from a start to an end constellation. This new approach combines trajectory approximation based on model predictive control... |
Towards an Online RRT-based Path Planning Algorithm for Ackermann-steering Vehicles | https://ieeexplore.ieee.org/document/9561207/ | [
"Jie Peng",
"Yu’An Chen",
"Yifan Duan",
"Yu Zhang",
"Jianmin Ji",
"Yanyong Zhang",
"Jie Peng",
"Yu’An Chen",
"Yifan Duan",
"Yu Zhang",
"Jianmin Ji",
"Yanyong Zhang"
] | It is challenging to develop an online path planning algorithm for Ackermann-steering vehicles to find collision-free and kinematically-feasible paths, that is efficient for dense environments, adaptable to various environments, and suitable for environments with narrow passages. In this paper, we propose a kinematically constrained RRT-based path planning algorithm integrating with a trajectory p... |
Three-dimensional Positioning of the Micropipette for Intracytoplasmic Sperm Injection | https://ieeexplore.ieee.org/document/9561549/ | [
"Weikang Hu",
"Haoyue Liang",
"Jianjie Li",
"Zhen Zhan",
"Yi Zhang",
"Chengzhi Hu",
"Weikang Hu",
"Haoyue Liang",
"Jianjie Li",
"Zhen Zhan",
"Yi Zhang",
"Chengzhi Hu"
] | ICSI (Intracytoplasmic sperm injection) is one of the most effective treatments for severe male infertility. During the implementation of the ICSI, it is necessary to perform the three-dimensional positioning of the tip of the glass injection micropipette. At present, the process is mainly controlled by skilled operators. Such manual operation is time-consuming and likely to cause micropipette dam... |
Robotic Cardinal Vein Microinjection of Zebrafish Larvae Based on 3D Positioning | https://ieeexplore.ieee.org/document/9561991/ | [
"Mingzhu Sun",
"Lu Li",
"Yatong Yao",
"Yiwen Wang",
"Huiying Gong",
"Qian Gao",
"Dongyan Chen",
"Xin Zhao",
"Mingzhu Sun",
"Lu Li",
"Yatong Yao",
"Yiwen Wang",
"Huiying Gong",
"Qian Gao",
"Dongyan Chen",
"Xin Zhao"
] | Zebrafish (Danio Rerio) larvae have long been an important model organism for biomedicine and drug discovery. It is difficult to deliver the external materials into the circulatory system by conventional exposing administration, while vein microinjection is more efficient but more challenging. In this paper, a robotic cardinal vein microinjection system was presented for zebrafish larvae. The key ... |
A Bipolar Myoelectric Sensor-Enabled Human-Machine Interface Based On Spinal Module Activations | https://ieeexplore.ieee.org/document/9561535/ | [
"Chunzhi Yi",
"Feng Jiang",
"Guangming Lu",
"Chifu Yang",
"Zhen Ding",
"Jianfei Zhu",
"Jie Liu",
"Chunzhi Yi",
"Feng Jiang",
"Guangming Lu",
"Chifu Yang",
"Zhen Ding",
"Jianfei Zhu",
"Jie Liu"
] | The surface electromyography (sEMG) signal-based human-machine interface (HMI) has been widely used for various scenarios of physical human-robot interaction. However, current HMIs based on bipolar myoelectric sensors are hindered by the limitations of global sEMG features, which are prone to variability and delay. In this letter, we define a HMI that takes advantage of the underlying neural infor... |
Enhancement for Robustness of Koopman Operator-based Data-driven Mobile Robotic Systems | https://ieeexplore.ieee.org/document/9561343/ | [
"Lu Shi",
"Konstantinos Karydis",
"Lu Shi",
"Konstantinos Karydis"
] | Koopman operator theory has served as the basis to extract dynamics for nonlinear system modeling and control across settings, including non-holonomic mobile robot control. There is a growing interest in research to derive robustness (and/or safety) guarantees for systems the dynamics of which are extracted via the Koopman operator. In this paper, we propose a way to quantify the prediction error ... |
Collision Risk Assessment and Obstacle Avoidance Control for Autonomous Sailing Robots | https://ieeexplore.ieee.org/document/9560859/ | [
"Weimin Qi",
"Qinbo Sun",
"Chongfeng Liu",
"Xiaoqiang Ji",
"Zhongzhong Cao",
"Yiwen Liang",
"Huihuan Qian",
"Weimin Qi",
"Qinbo Sun",
"Chongfeng Liu",
"Xiaoqiang Ji",
"Zhongzhong Cao",
"Yiwen Liang",
"Huihuan Qian"
] | Obstacle avoidance is crucial for autonomous surface vehicles (ASVs) in the sea because rescue is extremely difficult there. OceanVoy, a sailboat toward long range energy-saving voyage, has to overcome the dual challenges, i.e. from the environmental interference and its low mobility preventing from precise obstacle avoidance. We propose a control scheme based on real-time collision risk assessmen... |
MSTC∗:Multi-robot Coverage Path Planning under Physical Constrain | https://ieeexplore.ieee.org/document/9561371/ | [
"Jingtao Tang",
"Chun Sun",
"Xinyu Zhang",
"Jingtao Tang",
"Chun Sun",
"Xinyu Zhang"
] | For large-scale tasks, coverage path planning (CPP) can benefit greatly from multiple robots. In this paper, we present an efficient algorithm MSTC∗ for multi-robot coverage path planning (mCPP) based on spiral spanning tree coverage (Spiral-STC). Our algorithm incorporates strict physical constraints like terrain traversability and material load capacity. We compare our algorithm against the stat... |
Impact Mitigation for Dynamic Legged Robots with Steel Wire Transmission Using Nonlinear Active Compliance Control | https://ieeexplore.ieee.org/document/9561641/ | [
"Junjie Yang",
"Hao Sun",
"Hao An",
"Changhong Wang",
"Junjie Yang",
"Hao Sun",
"Hao An",
"Changhong Wang"
] | Impact mitigation is crucial to the stable locomotion of legged robots, especially in high-speed dynamic locomotion. This paper presents a leg locomotion system, including the nonlinear active compliance control and the active impedance control for the steel wire transmission-based legged robot. The developed control system enables high-speed dynamic locomotion with excellent impact mitigation and... |
Robust Improvement in 3D Object Landmark Inference for Semantic Mapping | https://ieeexplore.ieee.org/document/9561596/ | [
"Xubin Lin",
"Yirui Yang",
"Li He",
"Weinan Chen",
"Yisheng Guan",
"Hong Zhang",
"Xubin Lin",
"Yirui Yang",
"Li He",
"Weinan Chen",
"Yisheng Guan",
"Hong Zhang"
] | Recent works on semantic Simultaneous Localization and Mapping (SLAM) utilizing object landmarks have shown superiority in terms of robustness and accuracy in tracking and localization. 3D object landmarks represented by a cubic or quadric surface are inferred from 2D object bounding boxes which are typically captured from multiple views by an object detector. Nevertheless, bounding box noises and... |
YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection | https://ieeexplore.ieee.org/document/9561423/ | [
"Yuxuan Liu",
"Lujia Wang",
"Ming Liu",
"Yuxuan Liu",
"Lujia Wang",
"Ming Liu"
] | Object detection in 3D with stereo cameras is an important problem in computer vision, and is particularly crucial in low-cost autonomous mobile robots without LiDARs. Nowadays, most of the best-performing frameworks for stereo 3D object detection are based on dense depth reconstruction from disparity estimation, making them extremely computationally expensive. To enable real-world deployments of ... |
Sliding Mode Control of the Semi-active Hover Backpack Based on the Bioinspired Skyhook Damper Model | https://ieeexplore.ieee.org/document/9561495/ | [
"Bin Zhang",
"Tao Liu",
"Wu Fan",
"Jinyuan Zhang",
"Bin Zhang",
"Tao Liu",
"Wu Fan",
"Jinyuan Zhang"
] | It is inevitable for human to bear the gravitational and inertial force when carrying loads. The impact force exerted on human body is originated from the inertial force which can increase the energy expenditure and cause injury to human body. This paper proposes a semi-active hover backpack with controllable air damper to minimize the inertial force. The skyhook damper model of hover backpack is ... |
Fast Light Show Design Platform for K-12 Children | https://ieeexplore.ieee.org/document/9561445/ | [
"Pengda Mao",
"Yan Gao",
"Bo Wang",
"An Yan",
"Xiaoyu Chi",
"Quan Quan",
"Pengda Mao",
"Yan Gao",
"Bo Wang",
"An Yan",
"Xiaoyu Chi",
"Quan Quan"
] | This paper aims to present a drone swarm light show design platform to support STEAM (science, technology, engineering, art and mathematics) education for K-12 children. With this platform, children can use this platform to design a drone swarm light show easily. To this end, the architecture of this platform contents three layers: UI layer, command layer, and physical layer. The UI layer has an e... |
Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning | https://ieeexplore.ieee.org/document/9561049/ | [
"Yunlong Song",
"HaoChih Lin",
"Elia Kaufmann",
"Peter Dürr",
"Davide Scaramuzza",
"Yunlong Song",
"HaoChih Lin",
"Elia Kaufmann",
"Peter Dürr",
"Davide Scaramuzza"
] | Professional race-car drivers can execute extreme overtaking maneuvers. However, existing algorithms for autonomous overtaking either rely on simplified assumptions about the vehicle dynamics or try to solve expensive trajectory-optimization problems online. When the vehicle approaches its physical limits, existing model-based controllers struggle to handle highly nonlinear dynamics, and cannot le... |
An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG Sensors | https://ieeexplore.ieee.org/document/9561227/ | [
"Shaoping Huang",
"Anzhu Gao",
"Zicong Wu",
"Chuqian Lou",
"Yanjun Wang",
"Guang-Zhong Yang",
"Shaoping Huang",
"Anzhu Gao",
"Zicong Wu",
"Chuqian Lou",
"Yanjun Wang",
"Guang-Zhong Yang"
] | MRI-guided robotic systems are emerging platforms for minimally invasive intervention because of high positioning accuracy and excellent tissue contrast. MR safe encoders are critical components for closed-loop robotic control. This paper develops an MR safe absolute rotary encoder based on eccentric sheave and FBG sensors. The eccentric sheave transforms the rotational motion of the shaft to the ... |
Elastic and Efficient LiDAR Reconstruction for Large-Scale Exploration Tasks | https://ieeexplore.ieee.org/document/9561736/ | [
"Yiduo Wang",
"Nils Funk",
"Milad Ramezani",
"Sotiris Papatheodorou",
"Marija Popović",
"Marco Camurri",
"Stefan Leutenegger",
"Maurice Fallon",
"Yiduo Wang",
"Nils Funk",
"Milad Ramezani",
"Sotiris Papatheodorou",
"Marija Popović",
"Marco Camurri",
"Stefan Leutenegger",
"Maurice Fallon"
] | We present an efficient, elastic 3D LiDAR reconstruction framework which can reconstruct up to maximum Li-DAR ranges (60 m) at multiple frames per second, thus enabling robot exploration in large-scale environments. Our approach only requires a CPU. We focus on three main challenges of large-scale reconstruction: integration of long-range LiDAR scans at high frequency, the capacity to deform the r... |
KFS-LIO: Key-Feature Selection for Lightweight Lidar Inertial Odometry | https://ieeexplore.ieee.org/document/9561324/ | [
"Wei Li",
"Yu Hu",
"Yinhe Han",
"Xiaowei Li",
"Wei Li",
"Yu Hu",
"Yinhe Han",
"Xiaowei Li"
] | Feature-based lidar odometry methods have attracted increasing attention due to their low computational cost. However, theoretically analysis of the effect of extracted features on pose estimation is still lacked. In this paper, we propose a method of key-feature selection for lightweight lidar inertial odometry, KFS-LIO, to further enhance the real-time performance by selecting the most effective... |
CamVox: A Low-cost and Accurate Lidar-assisted Visual SLAM System | https://ieeexplore.ieee.org/document/9561149/ | [
"Yuewen Zhu",
"Chunran Zheng",
"Chongjian Yuan",
"Xu Huang",
"Xiaoping Hong",
"Yuewen Zhu",
"Chunran Zheng",
"Chongjian Yuan",
"Xu Huang",
"Xiaoping Hong"
] | Combining lidar in camera-based simultaneous localization and mapping (SLAM) is an effective method in improving overall accuracy, especially at outdoor large scale scenes. Recent development of low-cost lidars (e.g. Livox lidar) enable us to explore such SLAM systems with lower budget and higher performance. In this paper we propose CamVox by adapting Livox lidars into visual SLAM (ORB-SLAM2) by ... |
PSF-LO: Parameterized Semantic Features Based Lidar Odometry | https://ieeexplore.ieee.org/document/9561554/ | [
"Guibin Chen",
"Bosheng Wang",
"Xiaoliang Wang",
"Huanjun Deng",
"Bing Wang",
"Shuo Zhang",
"Guibin Chen",
"Bosheng Wang",
"Xiaoliang Wang",
"Huanjun Deng",
"Bing Wang",
"Shuo Zhang"
] | Lidar odometry (LO) is a key technology in numerous reliable and accurate localization and mapping systems of autonomous driving. The state-of-the-art LO methods generally leverage geometric information to perform point cloud registration. Furthermore, obtaining the point cloud semantic information describing the environment more abundantly will facilitate the registration. We present a novel sema... |
Relational Navigation Learning in Continuous Action Space among Crowds | https://ieeexplore.ieee.org/document/9561884/ | [
"Xueyou Zhang",
"Wei Xi",
"Xian Guo",
"Yongchun Fang",
"Bin Wang",
"Wulong Liu",
"Jianye Hao",
"Xueyou Zhang",
"Wei Xi",
"Xian Guo",
"Yongchun Fang",
"Bin Wang",
"Wulong Liu",
"Jianye Hao"
] | In this paper, a novel navigation learning method in continuous action space among crowds based on relational graph is proposed which can be directly deployed on differential-drive mobile robots without any change. More specifically, in order to increase generalization ability in crowd sizes, Graph Convolutional Network (GCN) is at first adopted to extract the relationships between robot and pedes... |
Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty | https://ieeexplore.ieee.org/document/9561843/ | [
"Richard Cheng",
"Richard M. Murray",
"Joel W. Burdick",
"Richard Cheng",
"Richard M. Murray",
"Joel W. Burdick"
] | When autonomous robots interact with humans, such as during autonomous driving, explicit safety guarantees are crucial in order to avoid potentially life-threatening accidents. Many data-driven methods have explored learning probabilistic bounds over human agents’ trajectories (i.e. confidence tubes that contain trajectories with probability δ), which can then be used to guarantee safety with prob... |
Probabilistic Human Motion Prediction via A Bayesian Neural Network | https://ieeexplore.ieee.org/document/9561665/ | [
"Jie Xu",
"Xingyu Chen",
"Xuguang Lan",
"Nanning Zheng",
"Jie Xu",
"Xingyu Chen",
"Xuguang Lan",
"Nanning Zheng"
] | Human motion prediction is an important and challenging topic that has promising prospects in efficient and safe human-robot-interaction systems. Currently, the majority of the human motion prediction algorithms are based on deterministic models, which may lead to risky decisions for robots. To solve this problem, we propose a probabilistic model for human motion prediction in this paper. The key ... |
Directed Acyclic Graph Neural Network for Human Motion Prediction | https://ieeexplore.ieee.org/document/9561540/ | [
"Qin Li",
"Georgia Chalvatzaki",
"Jan Peters",
"Yong Wang",
"Qin Li",
"Georgia Chalvatzaki",
"Jan Peters",
"Yong Wang"
] | Human motion prediction is essential in human-robot interaction. Current research mostly considers the joint dependencies but ignores the bone dependencies and their relationship in the human skeleton, thus limiting the prediction accuracy. To address this issue, we represent the human skeleton as a directed acyclic graph with joints as vertexes and bones as directed edges. Then, we propose a nove... |
Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraints | https://ieeexplore.ieee.org/document/9561012/ | [
"Yixuan Wang",
"Dale McConachie",
"Dmitry Berenson",
"Yixuan Wang",
"Dale McConachie",
"Dmitry Berenson"
] | In order to manipulate a deformable object, such as rope or cloth, in unstructured environments, robots need a way to estimate its current shape. However, tracking the shape of a deformable object can be challenging because of the object’s high flexibility, (self-)occlusion, and interaction with obstacles. Building a high-fidelity physics simulation to aid in tracking is difficult for novel enviro... |
Online Recommendation-based Convolutional Features for Scale-Aware Visual Tracking | https://ieeexplore.ieee.org/document/9562065/ | [
"Ran Duan",
"Changhong Fu",
"Kostas Alexis",
"Erdal Kayacan",
"Ran Duan",
"Changhong Fu",
"Kostas Alexis",
"Erdal Kayacan"
] | In this paper, we develop an online learning-based visual tracking framework that can optimize the target model and estimate the scale variation for object tracking. We propose a recommender-based tracker, which is capable of selecting the representative convolutional neural network (CNN) layers and feature maps autonomously. In addition, the proposed recommender computes the weights of these laye... |
Exploiting Probabilistic Siamese Visual Tracking with a Conditional Variational Autoencoder | https://ieeexplore.ieee.org/document/9561757/ | [
"Wenhui Huang",
"Jason Gu",
"Peiyong Duan",
"Sujuan Hou",
"Yuanjie Zheng",
"Wenhui Huang",
"Jason Gu",
"Peiyong Duan",
"Sujuan Hou",
"Yuanjie Zheng"
] | Visual tracking is a fundamental capability for robots tasked with humans and environment interaction. However, state-of-the-art visual tracking methods are still prone to failures and are imprecise when applied to challenging stereos, and their results are generally confidence agonistic. These methods depend on an embedded deep learning model to provide deterministic features or regression maps. ... |
Toward intraoperative endomicroscopy with a GPU-accelerated deformable video mosaicking algorithm | https://ieeexplore.ieee.org/document/9561975/ | [
"Lun Gong",
"Siyang Zuo",
"Lun Gong",
"Siyang Zuo"
] | Due to the limited field of view (FOV), the probe-based confocal laser endomicroscopy (pCLE) imaging system remains challenging to be widely used in clinic. Existing video mosaicking approaches are usually troubled by poor real-time capability and sensitivity to tissue deformations and intensity fluctuations. In this paper, a novel pCLE mosaicking algorithm that simultaneously implements rigid pro... |
Cutting Depth Compensation Based on Milling Acoustic Signal for Robotic-Assisted Laminectomy | https://ieeexplore.ieee.org/document/9561427/ | [
"Guangming Xia",
"Bin Yao",
"Yu Dai",
"Jianxun Zhang",
"Guangming Xia",
"Bin Yao",
"Yu Dai",
"Jianxun Zhang"
] | To optimize the cutting depth in robotic-assisted laminectomy, we present a real-time method to adjust the preoperatively planned feed rate in the depth direction of the robot cutting trajectory. Not only the linearity between the harmonic amplitude of the milling acoustic signal and the cutting depth is discussed by analyzing the milling dynamic model, but its influencing variables are analyzed. ... |
UMLE: Unsupervised Multi-discriminator Network for Low Light Enhancement | https://ieeexplore.ieee.org/document/9561051/ | [
"Yangyang Qu",
"Kai Chen",
"Chao Liu",
"Yongsheng Ou",
"Yangyang Qu",
"Kai Chen",
"Chao Liu",
"Yongsheng Ou"
] | Low-light image enhancement is a complex and vital task including, recovering color and texture details from low-light images. For automated driving, low-light scenarios will have severe implications for vision-based applications. To address this problem, we propose a real-time unsupervised generative adversarial network (GAN) with multiple discriminators. It includes a multi-scale discriminator, ... |
Unsupervised Learning of 3D Scene Flow from Monocular Camera | https://ieeexplore.ieee.org/document/9561572/ | [
"Guangming Wang",
"Xiaoyu Tian",
"Ruiqi Ding",
"Hesheng Wang",
"Guangming Wang",
"Xiaoyu Tian",
"Ruiqi Ding",
"Hesheng Wang"
] | Scene flow represents the motion of points in the 3D space, which is the counterpart of the optical flow that represents the motion of pixels in the 2D image. However, it is difficult to obtain the ground truth of scene flow in the real scenes, and recent studies are based on synthetic data for training. Therefore, how to train a scene flow network with unsupervised methods based on real-world dat... |
Deep3DRanker: A Novel Framework for Learning to Rank 3D Models with Self-Attention in Robotic Vision | https://ieeexplore.ieee.org/document/9561732/ | [
"Frank Po Wen Lo",
"Yao Guo",
"Yingnan Sun",
"Jianing Qiu",
"Benny Lo",
"Frank Po Wen Lo",
"Yao Guo",
"Yingnan Sun",
"Jianing Qiu",
"Benny Lo"
] | Research on generating or processing point clouds has become an increasingly popular domain in robotic research due to its extensive applications, such as robotic grasping, augmented reality and autonomous vehicle navigation. In this paper, we explore a new research area on point clouds - Learning to rank 3D models captured from a single depth image. In the Learning To Rank (LTR) task, we aim at o... |
FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection | https://ieeexplore.ieee.org/document/9561245/ | [
"Yi Wei",
"Shang Su",
"Jiwen Lu",
"Jie Zhou",
"Yi Wei",
"Shang Su",
"Jiwen Lu",
"Jie Zhou"
] | In this paper, we investigate the problem of weakly supervised 3D vehicle detection. Conventional methods for 3D object detection usually require vast amounts of manually labelled 3D data as supervision signals. However, annotating large datasets needs huge human efforts, especially for 3D area. To tackle this problem, we propose a frustum-aware geometric reasoning (FGR) method to detect vehicles ... |
Towards Collision Detection, Localization and Force Estimation for a Soft Cable-driven Robot Manipulator | https://ieeexplore.ieee.org/document/9560779/ | [
"Yuxin Wang",
"Hesheng Wang",
"Fan Xu",
"Junzhi Yu",
"Weidong Chen",
"Yun-Hui Liu",
"Yuxin Wang",
"Hesheng Wang",
"Fan Xu",
"Junzhi Yu",
"Weidong Chen",
"Yun-Hui Liu"
] | Soft robots have been applied widely to various constrained scenarios due to the advantages over traditional rigid manipulators such as softness, deformability and adaptability to constrained surroundings. To make full use of this merit, this paper proposes a method that integrates collision detection, localization and force estimation for a cable-driven soft manipulator without any prior geometri... |
Kinematic analysis of a flexible surgical instrument for robot-assisted minimally invasive surgery | https://ieeexplore.ieee.org/document/9561634/ | [
"Mei Feng",
"Zhixue Ni",
"Yili Fu",
"Xingze Jin",
"Wei Liu",
"Xiuquan Lu",
"Mei Feng",
"Zhixue Ni",
"Yili Fu",
"Xingze Jin",
"Wei Liu",
"Xiuquan Lu"
] | Flexible surgical instruments can flexibly adjust their posture with a high degree of freedom, which makes them highly suitable for performing surgical tasks in narrow workspaces. However, redundant degrees of freedom increase their kinematic difficulty, which may cause redundant solutions, complex calculations, and low speeds. In this paper, a flexible surgical instrument is presented. The struct... |
ENCODE: a dEep poiNt Cloud ODometry nEtwork | https://ieeexplore.ieee.org/document/9562024/ | [
"Yihuan Zhang",
"Liang Wang",
"Chen Fu",
"Yifan Dai",
"John M. Dolan",
"Yihuan Zhang",
"Liang Wang",
"Chen Fu",
"Yifan Dai",
"John M. Dolan"
] | Ego-motion estimation is a key requirement for the simultaneous localization and mapping (SLAM) problem. The traditional pipeline goes through feature extraction, feature matching and pose estimation, whose performance depends on the manually designed features. In this paper, we are motivated by the strong performance of deep learning methods in other computer vision and robotics tasks. We replace... |
CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth | https://ieeexplore.ieee.org/document/9560792/ | [
"Xingxing Zuo",
"Nathaniel Merrill",
"Wei Li",
"Yong Liu",
"Marc Pollefeys",
"Guoquan Huang",
"Xingxing Zuo",
"Nathaniel Merrill",
"Wei Li",
"Yong Liu",
"Marc Pollefeys",
"Guoquan Huang"
] | In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth maps of the immediate surroundings. Leveraging the proposed lightweight Conditional Variational Autoencoder (CVAE) for depth inference and encoding, we provide the network with previously marginalized sparse features from V... |
Lifelong Localization in Semi-Dynamic Environment | https://ieeexplore.ieee.org/document/9561584/ | [
"Shifan Zhu",
"Xinyu Zhang",
"Shichun Guo",
"Jun Li",
"Huaping Liu",
"Shifan Zhu",
"Xinyu Zhang",
"Shichun Guo",
"Jun Li",
"Huaping Liu"
] | Mapping and localization in non-static environments are fundamental problems in robotics. Most of previous methods mainly focus on static and highly dynamic objects in the environment, which may suffer from localization failure in semi-dynamic scenarios without considering objects with lower dynamics, such as parked cars and stopped pedestrians. In this paper, we introduce semantic mapping and lif... |
Deep Online Correction for Monocular Visual Odometry | https://ieeexplore.ieee.org/document/9561642/ | [
"Jiaxin Zhang",
"Wei Sui",
"Xinggang Wang",
"Wenming Meng",
"Hongmei Zhu",
"Qian Zhang",
"Jiaxin Zhang",
"Wei Sui",
"Xinggang Wang",
"Wenming Meng",
"Hongmei Zhu",
"Qian Zhang"
] | In this work, we propose a novel deep online correction (DOC) framework for monocular visual odometry. The whole pipeline has two stages: First, depth maps and initial poses are obtained from convolutional neural networks (CNNs) trained in self-supervised manners. Second, the poses predicted by CNNs are further improved by minimizing photometric errors via gradient updates of poses during inferenc... |
Direct Sparse Stereo Visual-Inertial Global Odometry | https://ieeexplore.ieee.org/document/9561410/ | [
"Ziqiang Wang",
"Mei Li",
"Dingkun Zhou",
"Ziqiang Zheng",
"Ziqiang Wang",
"Mei Li",
"Dingkun Zhou",
"Ziqiang Zheng"
] | Robust and accurate localization plays a key role in autonomous driving and robot applications. To utilize the complementary properties of different sensors, we present a novel tightly-coupled approach to combine the local (stereo cameras, IMU) and global sensors (magnetometer, GNSS). We jointly optimize all the model parameters through one active window. The visual part integrates constraints fro... |
Adversarially-trained Hierarchical Feature Extractor for Vehicle Re-identification | https://ieeexplore.ieee.org/document/9561632/ | [
"Pranjay Shyam",
"Kuk-Jin Yoon",
"Kyung-Soo Kim",
"Pranjay Shyam",
"Kuk-Jin Yoon",
"Kyung-Soo Kim"
] | Vehicle Re-identification (Re-ID) aims to retrieve all instances of query vehicle images present in an image pool. However viewpoint, illumination, and occlusion variations along with subtle differences between two unique images pose a significant challenge towards achieving an effective system. In this paper, we emphasize upon enhancing the performance of visual feature based ReID system by impro... |
VIC-Net: Voxelization Information Compensation Network for Point Cloud 3D Object Detection | https://ieeexplore.ieee.org/document/9561597/ | [
"Tianyuan Jiang",
"Nan Song",
"Huanyu Liu",
"Ruihao Yin",
"Ye Gong",
"Jian Yao",
"Tianyuan Jiang",
"Nan Song",
"Huanyu Liu",
"Ruihao Yin",
"Ye Gong",
"Jian Yao"
] | Voxel-based methods have been widely used in point cloud 3D object detection. These methods usually transform points into voxels while suffering from information loss during point cloud voxelization. To address this problem, we propose a novel one-stage Voxelization Information Compensation Network (VIC-Net), which has the ability of loss-free feature extraction. The whole framework consists of a ... |
Semantic Reinforced Attention Learning for Visual Place Recognition | https://ieeexplore.ieee.org/document/9561812/ | [
"Guohao Peng",
"Yufeng Yue",
"Jun Zhang",
"Zhenyu Wu",
"Xiaoyu Tang",
"Danwei Wang",
"Guohao Peng",
"Yufeng Yue",
"Jun Zhang",
"Zhenyu Wu",
"Xiaoyu Tang",
"Danwei Wang"
] | Large-scale visual place recognition (VPR) is inherently challenging because not all visual cues in the image are beneficial to the task. In order to highlight the task-relevant visual cues in the feature embedding, the existing attention mechanisms are either based on artificial rules or trained in a thorough data-driven manner. To fill the gap between the two types, we propose a novel Semantic R... |
Towards Efficient Multiview Object Detection with Adaptive Action Prediction | https://ieeexplore.ieee.org/document/9561388/ | [
"Qianli Xu",
"Fen Fang",
"Nicolas Gauthier",
"Wenyu Liang",
"Yan Wu",
"Liyuan Li",
"Joo-Hwee Lim",
"Qianli Xu",
"Fen Fang",
"Nicolas Gauthier",
"Wenyu Liang",
"Yan Wu",
"Liyuan Li",
"Joo-Hwee Lim"
] | Active vision is a desirable perceptual feature for robots. Existing approaches usually make strong assumptions about the task and environment, thus are less robust and efficient. This study proposes an adaptive view planning approach to boost the efficiency and robustness of active object detection. We formulate the multi-object detection task as an active multiview object detection problem given... |
Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive Loss | https://ieeexplore.ieee.org/document/9561793/ | [
"Dongseok Shim",
"H. Jin Kim",
"Dongseok Shim",
"H. Jin Kim"
] | Estimating a depth map from a single RGB image has been investigated widely for localization, mapping, and 3- dimensional object detection. Recent studies on a single-view depth estimation are mostly based on deep Convolutional neural Networks (ConvNets) which require a large amount of training data paired with densely annotated labels. Depth annotation tasks are both expensive and inefficient, so... |
Stereo-augmented Depth Completion from a Single RGB-LiDAR image | https://ieeexplore.ieee.org/document/9561557/ | [
"Keunhoon Choi",
"Somi Jeong",
"Youngjung Kim",
"Kwanghoon Sohn",
"Keunhoon Choi",
"Somi Jeong",
"Youngjung Kim",
"Kwanghoon Sohn"
] | Depth completion is an important task in computer vision and robotics applications, which aims at predicting accurate dense depth from a single RGB-LiDAR image. Convolutional neural networks (CNNs) have been widely used for depth completion to learn a mapping function from sparse to dense depth. However, recent methods do not exploit any 3D geometric cues during the inference stage and mainly rely... |
PENet: Towards Precise and Efficient Image Guided Depth Completion | https://ieeexplore.ieee.org/document/9561035/ | [
"Mu Hu",
"Shuling Wang",
"Bin Li",
"Shiyu Ning",
"Li Fan",
"Xiaojin Gong",
"Mu Hu",
"Shuling Wang",
"Bin Li",
"Shiyu Ning",
"Li Fan",
"Xiaojin Gong"
] | Image guided depth completion is the task of generating a dense depth map from a sparse depth map and a high quality image. In this task, how to fuse the color and depth modalities plays an important role in achieving good performance. This paper proposes a two-branch backbone that consists of a color-dominant branch and a depth-dominant branch to exploit and fuse two modalities thoroughly. More s... |
Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving | https://ieeexplore.ieee.org/document/9561754/ | [
"Hsu-Kuang Chiu",
"Jie Li",
"Rareş Ambruş",
"Jeannette Bohg",
"Hsu-Kuang Chiu",
"Jie Li",
"Rareş Ambruş",
"Jeannette Bohg"
] | Multi-object tracking is an important ability for an autonomous vehicle to safely navigate a traffic scene. Current state-of-the-art follows the tracking-by-detection paradigm where existing tracks are associated with detected objects through some distance metric. Key challenges to increase tracking accuracy lie in data association and track life cycle management. We propose a probabilistic, multi... |
AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attention | https://ieeexplore.ieee.org/document/9560908/ | [
"Congcong Liu",
"Yuying Chen",
"Ming Liu",
"Bertram E. Shi",
"Congcong Liu",
"Yuying Chen",
"Ming Liu",
"Bertram E. Shi"
] | Pedestrian trajectory prediction is a critical yet challenging task especially for crowded scenes. We suggest that introducing an attention mechanism to infer the importance of different neighbors is critical for accurate trajectory prediction in scenes with varying crowd size. In this work, we propose a novel method, AVGCN, for trajectory prediction utilizing graph convolutional networks (GCN) ba... |
Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases | https://ieeexplore.ieee.org/document/9561480/ | [
"Kunming Li",
"Stuart Eiffert",
"Mao Shan",
"Francisco Gomez-Donoso",
"Stewart Worrall",
"Eduardo Nebot",
"Kunming Li",
"Stuart Eiffert",
"Mao Shan",
"Francisco Gomez-Donoso",
"Stewart Worrall",
"Eduardo Nebot"
] | Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion both accurately and with minimal delay. Understanding the uncertainty of the prediction is also crucial. Most existing approaches however can only estimate uncertainty through repeated sampling of generative models. Additionally, most current predictive models are trained on datasets... |
Spatial Graph Regularized Multi-kernel Subtask Cross-correlation Tracker | https://ieeexplore.ieee.org/document/9561264/ | [
"Baojie Fan",
"Baojie Fan"
] | Some impressing multi-kernel or multi-task correlation filter trackers only focus on boosting the discrimination of multi-channel features, or exploiting the interdependence among different tasks. However, the cooperation and complementary of both technologies are missed, and the spatial structure among or inside target regions is also ignored. Therefore, this paper proposes a spatial graph regula... |
A Large-Scale Dataset for Benchmarking Elevator Button Segmentation and Character Recognition | https://ieeexplore.ieee.org/document/9562109/ | [
"Jianbang Liu",
"Yuqi Fang",
"Delong Zhu",
"Nachuan Ma",
"Jin Pan",
"Max Q.-H. Meng",
"Jianbang Liu",
"Yuqi Fang",
"Delong Zhu",
"Nachuan Ma",
"Jin Pan",
"Max Q.-H. Meng"
] | Human activities are hugely restricted by COVID-19, recently. Robots that can conduct inter-floor navigation attract much public attention since they can substitute human workers to conduct the service work. However, current robots either depend on human assistance or elevator retrofitting, and fully autonomous inter-floor navigation is still not available. As the very first step of inter-floor na... |
Neighborhood Spatial Aggregation based Efficient Uncertainty Estimation for Point Cloud Semantic Segmentation | https://ieeexplore.ieee.org/document/9560972/ | [
"Chao Qi",
"Jianqin Yin",
"Huaping Liu",
"Jun Liu",
"Chao Qi",
"Jianqin Yin",
"Huaping Liu",
"Jun Liu"
] | Uncertainty estimation for point cloud semantic segmentation is to quantify the confidence degree for the predicted label of points, which is essential for decision-making tasks. This paper proposes a neighborhood spatial aggregation based method, NSA-MC dropout, to achieve efficient uncertainty estimation for point cloud semantic segmentation. Unlike the traditional uncertainty estimation method ... |
S3Net: 3D LiDAR Sparse Semantic Segmentation Network | https://ieeexplore.ieee.org/document/9561305/ | [
"Ran Cheng",
"Ryan Razani",
"Yuan Ren",
"Liu Bingbing",
"Ran Cheng",
"Ryan Razani",
"Yuan Ren",
"Liu Bingbing"
] | Semantic Segmentation is a crucial component in the perception systems of many applications, such as robotics and autonomous driving that rely on accurate environmental perception and understanding. In literature, several approaches are introduced to attempt LiDAR semantic segmentation task, such as projection-based (range-view or birds-eye-view), and voxel-based approaches. However, they either a... |
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation | https://ieeexplore.ieee.org/document/9560898/ | [
"Ziming Ding",
"Tiankai Yang",
"Kunyi Zhang",
"Chao Xu",
"Fei Gao",
"Ziming Ding",
"Tiankai Yang",
"Kunyi Zhang",
"Chao Xu",
"Fei Gao"
] | Recently, quadrotors are gaining significant attention in aerial transportation and delivery. In these scenarios, an accurate estimation of the external force is as essential as the six degree-of-freedom (DoF) pose since it is of vital importance for planning and control of the vehicle. To this end, we propose a tightly-coupled Visual-Inertial-Dynamics (VID) system that simultaneously estimates th... |
LIRO: Tightly Coupled Lidar-Inertia-Ranging Odometry | https://ieeexplore.ieee.org/document/9560954/ | [
"Thien-Minh Nguyen",
"Muqing Cao",
"Shenghai Yuan",
"Yang Lyu",
"Thien Hoang Nguyen",
"Lihua Xie",
"Thien-Minh Nguyen",
"Muqing Cao",
"Shenghai Yuan",
"Yang Lyu",
"Thien Hoang Nguyen",
"Lihua Xie"
] | In recent years, thanks to the continuously reduced cost and weight of 3D lidar, the applications of this type of sensor in the community have become increasingly popular. Despite many progresses, estimation drift and tracking loss are still prevalent concerns associated with these systems. However, in theory these issues can be resolved with the use of some observations to fixed landmarks in the ... |
Verbal Focus-of-Attention System for Learning-from-Observation | https://ieeexplore.ieee.org/document/9562102/ | [
"Naoki Wake",
"Iori Yanokura",
"Kazuhiro Sasabuchi",
"Katsushi Ikeuchi",
"Naoki Wake",
"Iori Yanokura",
"Kazuhiro Sasabuchi",
"Katsushi Ikeuchi"
] | The learning-from-observation (LfO) framework aims to map human demonstrations to a robot to reduce programming effort. To this end, an LfO system encodes a human demonstration into a series of execution units for a robot, which are referred to as task models. Although previous research has proposed successful task-model encoders, there has been little discussion on how to guide a task-model encod... |
Hybrid Model Control of WalkON Suit for Precise and Robust Gait Assistance of Paraplegics | https://ieeexplore.ieee.org/document/9561000/ | [
"Kyeong-Won Park",
"Jungsu Choi",
"Kyoungchul Kong",
"Kyeong-Won Park",
"Jungsu Choi",
"Kyoungchul Kong"
] | Powered exoskeletons for people with paraplegia have been widely developed. To generate the basic but essential motions for daily human life, precise control algorithms to follow the joint reference trajectories are necessary. The dynamic characteristics of the exoskeletal joints, however, varies signifi-cantly during walking because the load side is exchanged from legs in the air to the wearer’s ... |
A Novel Gait Phase Detection Algorithm for Foot Drop Correction through Optimal Hybrid FES-Orthosis Assistance | https://ieeexplore.ieee.org/document/9561497/ | [
"Pyeong-Gook Jung",
"Weiguang Huo",
"Huiseok Moon",
"Yacine Amirat",
"Samer Mohammed",
"Pyeong-Gook Jung",
"Weiguang Huo",
"Huiseok Moon",
"Yacine Amirat",
"Samer Mohammed"
] | As a life-threatening disease, stroke can lead to long-term problems affecting the patients’ daily living ability. A common problem facing post-stroke patients is foot drop. An emerging modality of interest for correcting the foot drop is to combine both actuated ankle-foot orthosis (AAFO) and functional electrical stimulation (FES). Such hybrid assistive system not only ensure effective assistanc... |
Rapid Pose Label Generation through Sparse Representation of Unknown Objects | https://ieeexplore.ieee.org/document/9561277/ | [
"Rohan P. Singh",
"Mehdi Benallegue",
"Yusuke Yoshiyasu",
"Fumio Kanehiro",
"Rohan P. Singh",
"Mehdi Benallegue",
"Yusuke Yoshiyasu",
"Fumio Kanehiro"
] | Deep Convolutional Neural Networks (CNNs) have been successfully deployed on robots for 6-DoF object pose estimation through visual perception. However, obtaining labeled data on a scale required for the supervised training of CNNs is a difficult task - exacerbated if the object is novel and a 3D model is unavailable. To this end, this work presents an approach for rapidly generating real-world, p... |
Learning to Predict Repeatability of Interest Points | https://ieeexplore.ieee.org/document/9561383/ | [
"Anh-Dzung Doan",
"Daniyar Turmukhambetov",
"Yasir Latif",
"Tat-Jun Chin",
"Soohyun Bae",
"Anh-Dzung Doan",
"Daniyar Turmukhambetov",
"Yasir Latif",
"Tat-Jun Chin",
"Soohyun Bae"
] | Many robotics applications require interest points that are highly repeatable under varying viewpoints and lighting conditions. However, this requirement is very challenging as the environment changes continuously and indefinitely, leading to appearance changes of interest points with respect to time. This paper proposes to predict the repeatability of an interest point as a function of time, whic... |
DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects | https://ieeexplore.ieee.org/document/9561100/ | [
"Rahul Sajnani",
"AadilMehdi Sanchawala",
"Krishna Murthy Jatavallabhula",
"Srinath Sridhar",
"K. Madhava Krishna",
"Rahul Sajnani",
"AadilMehdi Sanchawala",
"Krishna Murthy Jatavallabhula",
"Srinath Sridhar",
"K. Madhava Krishna"
] | We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images. Canonical shape reconstruction— estimating 3D object shape in a coordinate space canonicalized for scale, rotation, and translation parameters—is an emerging paradigm that holds promise for a multitude of robotic applications. Prior approaches either rely on painstakingly gathered ... |
FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation | https://ieeexplore.ieee.org/document/9560800/ | [
"Lingtong Kong",
"Chunhua Shen",
"Jie Yang",
"Lingtong Kong",
"Chunhua Shen",
"Jie Yang"
] | Dense optical flow estimation plays a key role in many robotic vision tasks. In the past few years, with the advent of deep learning, we have witnessed great progress in optical flow estimation. However, current networks often consist of a large number of parameters and require heavy computation costs, largely hindering its application on low power-consumption devices such as mobile phones. In thi... |
Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection | https://ieeexplore.ieee.org/document/9561778/ | [
"Junho Koh",
"Jaekyum Kim",
"Younji Shin",
"Byeongwon Lee",
"Seungji Yang",
"Jun Won Choi",
"Junho Koh",
"Jaekyum Kim",
"Younji Shin",
"Byeongwon Lee",
"Seungji Yang",
"Jun Won Choi"
] | In this paper, we propose a new video object detection (VoD) method, referred to as temporal feature aggregation and motion-aware VoD (TM-VoD), that produces a joint representation of temporal image sequences and object motion. The TM-VoD generates strong spatiotemporal features for VOD by temporally redundant information in an image sequence and the motion context. These are produced at the featu... |
Targetless Multiple Camera-LiDAR Extrinsic Calibration using Object Pose Estimation | https://ieeexplore.ieee.org/document/9560936/ | [
"Byung-Hyun Yoon",
"Hyeon-Woo Jeong",
"Kang-Sun Choi",
"Byung-Hyun Yoon",
"Hyeon-Woo Jeong",
"Kang-Sun Choi"
] | We propose a targetless method for calibrating the extrinsic parameters among multiple cameras and a LiDAR sensor using object pose estimation. Contrast to previous targetless methods requiring certain geometric features, the proposed method exploits any objects of unspecified shapes in the scene to estimate the calibration parameters in single-scan configuration. Semantic objects in the scene are... |
Toward a Unified Framework for Point Set Registration | https://ieeexplore.ieee.org/document/9561594/ | [
"Feiran Li",
"Kent Fujiwara",
"Yasuyuki Matsushita",
"Feiran Li",
"Kent Fujiwara",
"Yasuyuki Matsushita"
] | Point set registration plays a critical role in robotics and computer vision. Early methods considered registration as a purely geometric problem, presenting excellent extensibility for various tasks due to their explicit handling of correspondences; statistical methods were later introduced to handle noise. However, the two categories of algorithms have evolved independently without sharing much ... |
Robot Motion Control with Compressive Feedback | https://ieeexplore.ieee.org/document/9561080/ | [
"Congjian Li",
"Song Wang",
"Siyu Wang",
"Sheng Bi",
"Yisheng Guan",
"Ning Xi",
"Congjian Li",
"Song Wang",
"Siyu Wang",
"Sheng Bi",
"Yisheng Guan",
"Ning Xi"
] | Robot motion control aims to generate control inputs for a robotic system to track a planned trajectory. Feedback provided by sensors plays an essential role in motion control by improving system performance when external disturbances and/or initial errors exist. However, feedback signals, such as images are often of a large size, which imposes a heavy computational burden on the system. In this p... |
MFPN-6D : Real-time One-stage Pose Estimation of Objects on RGB Images | https://ieeexplore.ieee.org/document/9561878/ | [
"Penglei Liu",
"Qieshi Zhang",
"Jin Zhang",
"Fei Wang",
"Jun Cheng",
"Penglei Liu",
"Qieshi Zhang",
"Jin Zhang",
"Fei Wang",
"Jun Cheng"
] | 6D pose estimation of objects is an important part of robot grasping. The latest research trend on 6D pose estimation is to train a deep neural network to directly predict the 2D projection position of the 3D key points from the image, establish the corresponding relationship, and finally use Pespective-n-Point (PnP) algorithm performs pose estimation. The current challenge of pose estimation is t... |
A Novel Tactile Feedback System with On-Line Texture Decoding and Direct-Texture-Feedback | https://ieeexplore.ieee.org/document/9561724/ | [
"Kuniharu Sakurada",
"Gowrishankar Ganesh",
"Wenwei Yu",
"Kuniharu Sakurada",
"Gowrishankar Ganesh",
"Wenwei Yu"
] | Tactile perception on our fingers is a key sensory feedback that enables us to perceive and explore our world using our hands as probes, and is essential for efficient gripping and manipulation of objects. A tactile feedback system can therefore greatly improve the quality of life of individuals with partial or complete sensory loss like during stroke, or with artificial limbs after an amputation.... |
PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation | https://ieeexplore.ieee.org/document/9560776/ | [
"Noriaki Hirose",
"Satoshi Koide",
"Keisuke Kawano",
"Ruho Kondo",
"Noriaki Hirose",
"Satoshi Koide",
"Keisuke Kawano",
"Ruho Kondo"
] | We propose a novel objective for penalizing geometric inconsistencies and improving the depth and pose estimation performance of monocular camera images. Our objective is designed using the Wasserstein distance between two point clouds, estimated from images with different camera poses. The Wasserstein distance can impose a soft and symmetric coupling between two point clouds, which suitably maint... |
Real-Time Mesh Extraction from Implicit Functions via Direct Reconstruction of Decision Boundary | https://ieeexplore.ieee.org/document/9560749/ | [
"Wataru Kawai",
"Yusuke Mukuta",
"Tatsuya Harada",
"Wataru Kawai",
"Yusuke Mukuta",
"Tatsuya Harada"
] | The ability to estimate 3D object shape from a single image is vital to robotics and manufacturing. For instance, it enables iterative trial-and-error in simulated environments. In single-view reconstruction, implicit functions have demonstrated superior results over traditional methods. However, implicit functions suffer from the heavy computation of mesh extraction. This is due to the indirect m... |
Uncertainty-Aware Fast Curb Detection Using Convolutional Networks in Point Clouds | https://ieeexplore.ieee.org/document/9561358/ | [
"Younghwa Jung",
"Mingu Jeon",
"Chan Kim",
"Seung-Woo Seo",
"Seong-Woo Kim",
"Younghwa Jung",
"Mingu Jeon",
"Chan Kim",
"Seung-Woo Seo",
"Seong-Woo Kim"
] | Curb detection is an essential function of autonomous vehicles in urban areas. However, curbs are difficult to detect in complex urban environments in which many dynamic objects exist. Additionally, curbs appear in a variety of shapes and sizes. Previous studies have been based on the traditional pipeline, which consists of the extraction and aggregation of hand-crafted features that are then fed ... |
OCR-based Inventory Management Algorithms Robust to Damaged Images | https://ieeexplore.ieee.org/document/9561280/ | [
"Minseok Seo",
"Daehan Kim",
"Hyeyoon Kang",
"Donghyeon Cho",
"Dong-Geol Choi",
"Minseok Seo",
"Daehan Kim",
"Hyeyoon Kang",
"Donghyeon Cho",
"Dong-Geol Choi"
] | Accurate and fast inventory management algorithms are essential in the modern distribution industry. However, the configuration process of inventory management algorithms is very expensive, and the direct comprehensive management of inventory procedures is labor intensive and inaccurate. Therefore, in this paper, we propose an optical character recognition (OCR)-based inventory management algorith... |
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