ROAISYSep 13, 2021

Autonomous Navigation of Underactuated Bipedal Robots in Height-Constrained Environments

arXiv:2109.05714v436 citations
Originality Incremental advance
AI Analysis

This addresses the problem of enabling bipedal robots to navigate complex, confined spaces, which is incremental as it builds on existing planning and control methods for robotics.

The paper tackles autonomous navigation for bipedal robots in cluttered, height-constrained environments by developing an end-to-end framework with planners and a variable walking height controller, experimentally validating it on the Cassie robot to achieve safe obstacle avoidance and goal-reaching.

Navigating a large-scaled robot in unknown and cluttered height-constrained environments is challenging. Not only is a fast and reliable planning algorithm required to go around obstacles, the robot should also be able to change its intrinsic dimension by crouching in order to travel underneath height-constrained regions. There are few mobile robots that are capable of handling such a challenge, and bipedal robots provide a solution. However, as bipedal robots have nonlinear and hybrid dynamics, trajectory planning while ensuring dynamic feasibility and safety on these robots is challenging. This paper presents an end-to-end autonomous navigation framework which leverages three layers of planners and a variable walking height controller to enable bipedal robots to safely explore height-constrained environments. A vertically-actuated Spring-Loaded Inverted Pendulum (vSLIP) model is introduced to capture the robot's coupled dynamics of planar walking and vertical walking height. This reduced-order model is utilized to optimize for long-term and short-term safe trajectory plans. A variable walking height controller is leveraged to enable the bipedal robot to maintain stable periodic walking gaits while following the planned trajectory. The entire framework is tested and experimentally validated using a bipedal robot Cassie. This demonstrates reliable autonomy to drive the robot to safely avoid obstacles while walking to the goal location in various kinds of height-constrained cluttered environments.

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