Effective Trajectory Tracking with Convex-Optimization Based Obstacle-Avoidance Method for Continuum Robot
Ping Deng, Rui Peng, Duo Tang, Xiao Cao, Peng Lu
AI summary
Problem
Continuum robots require precise tip tracking while navigating dynamic, obstacle-filled spaces, but existing methods often suffer from high computational costs, poor scalability, or inability to handle moving or irregular obstacles.
Approach
The method models the robot and obstacles as convex polytopes, uses the GJK algorithm for rapid collision detection, and solves trajectory tracking via quadratic programming that enforces safety and joint constraints.
Key results
- Sub-10ms average computation time for inverse kinematics with obstacle avoidance
- Tip tracking error maintained under 2% across static and dynamic simulations
- Successful real-world validation on a three-segment cable-driven continuum robot prototype
- Real-time adaptability to moving obstacles and irregular 3D geometries
Why it matters
Provides a computationally efficient, safety-guaranteed control framework that advances the practical deployment of continuum robots in surgery and confined industrial tasks.
Abstract
A cable-driven continuum robot with high redun- dancy is capable of performing the tip trajectory tracking task while simultaneously satisfying additional safety constraints, such as joint limits or external obstacles in the environment. To address these challenges, efficient motion planning methods are required. This paper proposes a quadratic programming based method in conjunction with convex polytopes based distance computation. Our methodology integrates safety con- straints based on the robots’ posture states, thus enabling barriers evasion in dynamic situations. Simulation outcomes demonstrate effective trajectory tracking in the presence of various objects and provide a comprehensive performance evaluation based on the generated robot state. Finally, real- world experiment was conducted on a prototype of a three- segment cable-driven continuum manipulator, which confirmed the efficacy of the proposed obstacle avoidance approach. The approach is versatile and can be adapted to similar multiple segments cable-driven continuum robotic systems by designing the robot parameters, enabling the success of tip trajectory tracking tasks under complex obstacle conditions.