Topology-Informed Quasi-Static Motion Planning for Continuum Robots with Contacts

Area of Science:

• Robotics
• Control Theory
• Computational Geometry

Background:

• Continuum robots (CRs) offer high dexterity for cluttered environments.
• Their underactuated nature makes static configuration dependent on environmental contact modes.
• Obstacles induce a complex topology in the robot's configuration space.

Purpose of the Study:

• To characterize the configuration space topology induced by environmental obstacles.
• To develop a motion planning strategy using a simplified representation of the configuration space.
• To reduce computational load for exploration and pathfinding in complex environments.

Main Methods:

• Characterizing configuration space topology via a quotient structure with zero-actuation configurations.
• Representing the quotient space as a graph of configuration modes.
• Constructing a graph of convex sets in the free workspace.
• Employing tree search and convex optimization to identify candidate configurations.
• Utilizing elastic energy minimization to determine configuration modes.
• Implementing a motion planner that utilizes the quotient space graph for pathfinding.

Main Results:

• The proposed method successfully identifies the quotient space as a graph of configuration modes.
• A motion planner was developed that finds paths in the quotient space graph and translates them to continuous configuration space paths.
• Demonstrated effectiveness in complex 3D environments.

Conclusions:

• The quotient space approach provides an effective roadmap for continuum robot motion planning.
• This method significantly outperforms baseline approaches in terms of computation time and success rate.
• The approach offers a computationally efficient way to navigate complex, cluttered environments with continuum robots.