An Online Optimization-Based Trajectory Planning Approach for Cooperative Landing Tasks
Jingshan Chen, Lihan Xu, Henrik Ebel, Peter Eberhard
TL;DR
The paper tackles cooperative landing of a quadrotor on a ground robot by formulating a one-step, online optimization framework that jointly handles dynamics, constraints, and autonomous coordination via a complementarity constraint. Time-optimal control is achieved through a flexible time-grid optimization (Delta t_k) and a centralized decision mechanism, enabling real-time replanning with efficient computation using FATROP. Numerical studies and hardware experiments with a Crazyflie quadrotor and an omnidirectional ground robot demonstrate successful landings within a few seconds and sub-second planning times, supporting online adaptability. The approach advances practical multi-robot collaboration by providing fast, generalizable planning that integrates decision-making and feasibility within a single optimization framework.
Abstract
This paper presents a real-time trajectory planning scheme for a heterogeneous multi-robot system (consisting of a quadrotor and a ground mobile robot) for a cooperative landing task, where the landing position, landing time, and coordination between the robots are determined autonomously under the consideration of feasibility and user specifications. The proposed framework leverages the potential of the complementarity constraint as a decision-maker and an indicator for diverse cooperative tasks and extends it to the collaborative landing scenario. In a potential application of the proposed methodology, a ground mobile robot may serve as a mobile charging station and coordinates in real-time with a quadrotor to be charged, facilitating a safe and efficient rendezvous and landing. We verified the generated trajectories in simulation and real-world applications, demonstrating the real-time capabilities of the proposed landing planning framework.