An Online Optimization-Based Trajectory Planning Approach for Cooperative Landing Tasks

2025-02-19

AI Summary

This work addresses the real-time trajectory planning challenge for cooperative landing of heterogeneous multi-robot systems comprising quadcopters and ground mobile robots, requiring autonomous determination of landing positions, timing, and inter-robot coordination while satisfying dynamical feasibility, user-specified constraints, and adaptability to dynamic environments. Method: We propose a novel online trajectory planning framework that integrates nonlinear optimization, complementarity-constrained decision-making, and closed-loop control. To our knowledge, this is the first approach to incorporate complementarity constraints into the cooperative landing decision framework, enabling unified modeling of task-type classification and real-time coordination. Results: Extensive simulations and physical experiments demonstrate real-time performance (≥10 Hz planning frequency), high landing accuracy, rapid environmental responsiveness, and successful deployment in representative applications such as mobile charging station support.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Multiagent Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

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.

Problem

• Real-time trajectory planning for multi-robot systems
• Autonomous coordination for cooperative landing tasks
• Efficient rendezvous and landing using complementarity constraints

Innovation

• Real-time trajectory planning
• Complementarity constraint decision-making
• Heterogeneous multi-robot coordination