A Generalized Continuous Collision Detection Framework of Polynomial Trajectory for Mobile Robots in Cluttered Environments
Zeqing Zhang, Yinqiang Zhang, Ruihua Han, Liangjun Zhang and Jia Pan
Abstract
In this paper, we introduce a generalized continuous collision detection (CCD) framework for the mobile robot along the polynomial trajectory in cluttered environments including various static obstacle models. Specifically, we find that the collision conditions between robots and obstacles could be transformed into a set of polynomial inequalities, whose roots can be efficiently solved by the proposed solver. In addition, we test different types of mobile robots with various kinematic and dynamic constraints in our generalized CCD framework and validate that it allows the provable collision checking and can compute the exact time of impact. Furthermore, we combine our architecture with the path planner in the navigation system. Benefiting from our CCD method, the mobile robot is able to work safely in some challenging scenarios.
Workflow
The workflow of our generalized CCD framework, whose role in the real navigation system for mobile robots is presented as well.
Experiments
Quadrotor
Collision Checking of Quadrotor with the ellipsoids, cylinders, and polyhedra with triangular mesh.
Cable-driven parallel robot
The collision of cables with environments seriously affects the workspace of this robot.
Automated guided vehicle
AGV navigates with sparse polygonal obstacles.
Automated guided vehicle
AGV navigates in a narrow corridor.
Acknowledgement
The authors would like to thank the editors and anonymous reviewers for their valuable feedback.
The authors also thank Mr. Tianyu Liu, Mr. Hongkai Ye, Dr. Shuai Zhang, and Dr. D. TM Lau for meaningful discussions.
This work was supported by HKSAR Research Grants Council (RGC) General Research Fund (GRF) HKU 11202119, 11207818, and the Innovation and Technology Commission of the HKSAR Government under the InnoHK initiative.