Any-time randomized kinodynamic path planning algorithm in dynamic environments with application to quadrotor

Abstract

Kinodynamic path planning is an open challenge in unmanned autonomous vehicles and is considered an NP-Hard problem. Planning a feasible path for vertical take-off and landing quadrotor (VTOL-Q) from an initial state to a target state in 3D space by considering the environmental constraints such as moving obstacles avoidance and non-holonomic constraints such as hard bounds of VTOL-Q is the key motivation of this study. To this end, let us propose the any-time randomized kinodynamic (ATRK) path-planning algorithm applicable in the VTOL-Q. ATRK path-planning algorithm is based on the Rapidly-exploring random trees (RRT) and consists of three main components: High-level, mid-level, and low-level controller. The high-level controller utilizes a randomized sampling-based approach to generate offspring vertices for rapid exploring and expanding in the configuration space. The mid-level controller uses the any-time method to avoid collision with moving obstacles. The low-level controller with a six- DOF dynamic model accounts for the kinodynamic constraints of VTOL-Q in the randomized offspring vertices to plan a feasible path. Simulation results on three different test-scenario demonstrate the kinodynamic constraints of the VTOL-Q are integrated into the randomized offspring vertices. Also, in presence of moving obstacles, the ATRK re-plans the path in the local area as through an any-time approach.