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Comparison of Approaches for UAV Dynamics Consideration in Sampling Based Path Planning Methods

Deployment of autonomous UAVs in an indoor environment puts higher requirements for path planning algorithms due to the more complex nature of the environment (narrow crossings, absence of GNSS, smaller manoeuvring space, etc. …). Due to the manoeuvring of UAV between obstacles, it is required to consider its dynamics in the path planning process. Basic versions of sampling-based path planning methods such as RRT (rapidly exploring random trees) or PRM (probabilistic roadmaps) don’t consider the dynamics of the object we are planning a path for. In the past several approaches for path planning with dynamic constraints were developed. The first approach, randomized kino-dynamic planning, was presented for the first time. The main goal of this approach is to incrementally search state space as configuration space and find control input, that results in a collision-free trajectory. The second approach, presented in, utilizes differential flatness of UAV’s (quadrotor) equations of motions. Thus, it is possible to precisely follow the path previously generated by the path planning algorithm. The main task of this paper is to compare the mentioned approaches for path planning with kino-dynamic constraints and decide which one of them is more suitable for the path planning module of autonomous UAV that is currently being developed at the Institute of Robotics at the Slovak University of Technology.