Robot Squid Game: Quadrupedal Locomotion for Traversing Narrow Tunnels
For quadruped robots in search and rescue or infrastructure inspection, this work addresses the challenge of navigating narrow tunnels, though the approach is domain-specific and incremental.
Quadruped robots often fail to autonomously traverse confined 3D environments like tunnels. The authors introduce an RL framework with procedural environment generation and policy distillation, achieving consistent traversal in simulation and real-world experiments where conventional methods fail.
Quadruped robots demonstrate exceptional potential for navigating complex terrain in critical applications such as search and rescue missions and infrastructure inspection However autonomous traversal of confined 3D environments including tunnels caves and collapsed structures remains a significant challenge Existing methods often struggle with rigid gait patterns limited adaptability to diverse geometries and reliance on oversimplified environmental assumptions This paper introduces a Reinforcement Learning RL framework that combines procedural environment generation with policy distillation to enable robust locomotion across various tunnel configurations Our approach leverages a teacher student training paradigm where specialized expert policies trained on procedurally generated tunnel geometries transfer their knowledge to a unified student policy This strategy eliminates the need for complex reward shaping in end-to-end RL training simplifying the process by breaking down complicated tasks into smaller more manageable components that are easier for the robot to learn By synthesizing diverse tunnel structures during training and distilling navigation strategies into a generalizable policy our method achieves consistent traversal across complex spatial constraints where conventional approaches fail We demonstrate through both simulation and real world experiments that our method enables quadruped robots to successfully traverse challenging confined tunnel environments