Fast trajectory planning via the B-spline augmented virtual motion camouflage approach

Abstract

Nonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance. This paper proposes an improved version of the bio-inspired virtual motion camouflage (VMC) method, which is based on the natural phenomenon of motion camouflage. Currently, the VMC method offers fast solutions that fall close to the optimal solution, but the solution optimality is affected by a selected and fixed search space that is defined by a fixed polynomial type prey motion. To increase the flexibility of the search space and thus improve the solution optimality, this paper proposes using B-spline curves to represent the prey motion, in which the control points and thus the prey motion can be optimized. It is expected that the proposed B-spline augmented VMC method will improve the solution optimality without sacrificing the CPU time too much. A minimum time obstacle avoidance robot problem will be simulated to demonstrate the capabilities of the algorithm.