Title: A Planning and Control Framework for Humanoid Systems: Robust, Optimal, and Real-time Performance,
Abstract: Humanoid robots are increasingly demanded to operate in interactive and
human-surrounded environments while achieving sophisticated locomotion and
manipulation tasks. To accomplish these tasks, roboticists unremittingly seek
for advanced methods that generate whole-body coordination behaviors and
meanwhile fulfill various planning and control objectives. Undoubtedly, these
goals pose fundamental challenges to the robotics and control community. To
take an incremental step towards reducing the performance gap between
theoretical foundations and real implementations, we present a planning and
control framework for the humanoid, especially legged robots, for achieving
high performance and generating agile motions. A particular concentration is on
the robust, optimal and real-time performance. This framework constitutes three
hierarchical layers: First, we present a robust optimal phase-space planning
framework for dynamic legged locomotion over rough terrain. This framework is a
hybrid motion planner incorporating a series of pivotal components. Second, we
take a step toward formally synthesizing high-level reactive planners for
whole-body locomotion in constrained environments. We formulate a two-player
temporal logic game between the contact planner and its possibly-adversarial
environment. Third, we propose a distributed control architecture for the
latency-prone humanoid robotic systems. A central experimental phenomenon is
observed that the stability of high impedance distributed controllers is highly
sensitive to damping feedback delay but much less to stiffness feedback delay.
We pursue a detailed analysis of the distributed controllers where damping
feedback effort is executed in proximity to the control plant, and stiffness
feedback effort is implemented in a latency-prone centralized control process.