A Novel Collision-Free Navigation Approach for Multiple Nonholonomic Robots Based on ORCA and Linear MPC

• Main Authors: Run Mao, Hongli Gao, Liang Guo
• Format: Article in Journal/Newspaper
• Language: unknown
• Subjects: Orca
• Online Access: http://downloads.hindawi.com/journals/MPE/2020/4183427.pdf; http://downloads.hindawi.com/journals/MPE/2020/4183427.xml

In the study of collision-free navigation methods of multirobots, much attention has been paid to the constraints of external environment. However, most of the wheeled mobile robots are subjected to nonholonomic constraints. A collision between robots may occur if the nonholonomic constraints are neglected. This paper presents an improved approach to collision-free navigation for multi-nonholonomic robots. This approach combines the Optimal Reciprocal Collision Avoidance (ORCA) algorithm and Model Predictive Control (MPC) strategy. ORCA used a simple robot model, in which kinematics and dynamics are ignored. To cope with this problem, the MPC controller is introduced. In each ORCA step, the reference trajectory, reference control inputs, and “safe zones” are generated based on the new velocity. Consequently, the derived safe zone is transformed into the constraints of decision variables for a MPC controller. Finally, quadratic programming is used to solve the MPC problem by successive linearization of an error model of the mobile robot. Simulation results illustrate the effectiveness of the proposed method.