Over-constrained trajectory planning of 4WIS-4WID Robots with model reconstruction and iterative optimal control
TL;DR
Experimental results show that the proposed method improves computational efficiency and reduces steering wheel accelerations and traveling wheel jerks, indicating the potential of the proposed approach for efficient and smooth trajectory planning in complex and highly maneuverable 4WIS-4WID robotic applications.
Abstract
With the rapid advancement of artificial intelligence, the four-wheel independent steering and four-wheel independent drive mobile robots (4WIS-4WID) have attracted increasing attention due to their superior maneuverability. However, trajectory planning for such robots remains challenging because the over-constrained nature of the system, where the number of control variables exceeds the system’s degrees of freedom (DoF), leading to a highly coupled and nonlinear control problem. To address this issue, this paper proposes an iterative trajectory planning algorithm. First, the kinematic steering singularity and discontinuity are analyzed, and the kinematic model is reconstructed into a diagonally arranged dual-steering-wheel configuration. Based on this model, the trajectory planning problem is formulated as an optimal control problem (OCP) that incorporates kinematic constraints, boundary conditions, and collision-avoidance constraints through a two-circle geometric approximation and safe corridor method. Furthermore, an iterative optimization framework with a penalty relaxation strategy is developed to enhance numerical stability and ensure convergence to feasible solutions. Experimental results show that the proposed method improves computational efficiency and reduces steering wheel accelerations and traveling wheel jerks. These results indicate the potential of the proposed approach for efficient and smooth trajectory planning in complex and highly maneuverable 4WIS-4WID robotic applications.