Riemannian Optimization-based Whole-body Obstacle Avoidance for Mobile Continuum Robots in Cluttered Environments
Overview
This paper presents a unified planning and control framework inspired by biological systems like snakes and octopus arms, designed for mobile continuum robots operating in cluttered environments. The approach integrates long-horizon trajectory planning with real-time geometric refinement using A* search, minimum-jerk planning, and Riemannian optimization to coordinate base motion and continuum deformation while avoiding obstacles. Evaluation includes simulated pipe-traversal tasks and real-world experiments demonstrating improved motion consistency and adaptability.
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- arXiv Robotics — research abstractsSignalRiemannian Optimization-based Whole-body Obstacle Avoidance for Mobile Continuum Robots in Cluttered Environments
This paper presents a unified planning and control framework inspired by biological systems like snakes and octopus arms, designed for mobile continuum robots operating in cluttered environments. The approach integrates long-horizon trajectory planning with real-time geometric refinement using A* search, minimum-jerk planning, and Riemannian optimization to coordinate base motion and continuum deformation while avoiding obstacles. Evaluation includes simulated pipe-traversal tasks and real-world experiments demonstrating improved motion consistency and adaptability.
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