Planning and Control for Cable-routing with Dual-arm Robot

Paper i proceeding, 2022

In this paper, we propose a new framework for solving cable-routing problems with a dual-arm robot, where the objective is to clip a Deformable Linear Object (DLO) into several arbitrarily placed fixtures. The core of the framework is a task-space planner, which builds a roadmap from predefined tasks and employs a replanning strategy based on a genetic algorithm, if problems occur. The manipulation tasks are executed with either individual or coordinated control of the arms. Moreover, hierarchical quadratic programming is used to solve the inverse differential kinematics together with extra feasibility objectives. A vision system first identifies the desired fixture route and structure preserved registration estimates the state of the DLO in real-time. The framework is tested on real-world experiments with a YuMi robot, demonstrating a 90% success rate for 3 fixture problems.