Abstract
This paper presents an obstacle-avoidance trajectory tracking method based on a nonlinear model prediction, with a dynamic environment considered in the trajectory tracking of nonholonomic mobile robots for obstacle avoidance. In this method, collision avoidance is embedded into the trajectory tracking control problem as a nonlinear constraint of the position state, which changes with time to solve the obstacle-avoidance problem in dynamic environments. The CasADi toolkit was used in MATLAB to generate a real-time, efficient C++ code with inequality constraints to avoid collisions. Trajectory tracking and obstacle avoidance in dynamic and static environments are trialed using MATLAB and CasADi simulations, and the effectiveness of the proposed control algorithm is verified.
Highlights
With the continuous development of robot technology, various robots are being increasingly used in complex working environments
Heonyoung et al [27] proposed an obstacle-avoidance strategy based on model predictive control and optimized the optimization problem using gradient descent method, using an algorithm able to verify the tracking ability and obstacle-avoidance ability of the mobile robot but that does not consider the presence of a dynamic environment
Collision avoidance is embedded into the trajectory tracking control problem as a nonlinear constraint of the position state, which changes with time to solve the obstacle-avoidance problem in dynamic environments
Summary
With the continuous development of robot technology, various robots are being increasingly used in complex working environments. Heonyoung et al [27] proposed an obstacle-avoidance strategy based on model predictive control and optimized the optimization problem using gradient descent method, using an algorithm able to verify the tracking ability and obstacle-avoidance ability of the mobile robot but that does not consider the presence of a dynamic environment. The main contributions of this paper are the use of a discrete-time system model based on MPC to achieve trajectory tracking control and to avoid dynamic obstacle collisions. Based on this method, the controller is designed and the rules for dynamic obstacle avoidance are set.
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