A Time-Optimal Trajectory Planning Strategy for an Aircraft With a Suspended Payload via Optimization and Learning Approaches

In this article, a real-time interactive time-optimal trajectory planning (TOTP) strategy is proposed for aircraft slung-load systems, in which the practical performance is guaranteed by taking advantage of convex optimization and reinforcement learning (RL) techniques. To the best of our knowledge, it is the first TOTP solution for an aircraft suspension system subject to path, velocity, acceleration, and cable tension constraints, where a practice-oriented RL policy is designed to interact with the system online. Specifically, by exploring the differential flatness property of the system, the states are projected into path coordinate space, where all the physical constraints are formulated in the TOTP with convex forms. Then, the TOTP is transformed into a large sparse optimization problem after discretization, which can be efficiently solved using convex solvers. Subsequently, a deep RL network is designed to optimize the TOTP results, where efficient learning is achieved in the solution space, thereby guaranteeing practical reliability and strong robustness via online interaction in applications. In addition, by incorporating convex optimization and learning techniques, the gap between simulation and experiment is successfully bridged, where the physical feasibility and efficient learning are ensured in the framework. Finally, comparative simulations and experimental results are included to show the effectiveness of the proposed strategy.

I. Introduction

Vertical take-off and landing (VTOL) aircraft-based suspended payload manipulations have attracted high attention in the past decades due to its extensive utility in many applications, such as military transportation, disaster response, package delivery, and rescue mission [1]–[12]. Motion planning is one of the most crucial issues for maximizing the productivity of the system. Generally, the motion planning problem is considered in two stages, known as the hierarchical motion planning framework: the former is path planning, determining the geometric path accounting only for task specifications, while the complicated dynamics and physical constraints are considered in the latter stage to derive the velocity allocation. Various path generation methods can be adopted to solve the path planning problem for aircraft slung-load systems [13]–[15]. However, the time-optimal velocity allocation for the system is extremely challenging, where not only the nonlinear, strongly coupled dynamic constraints, but also the various uncertainties and disturbances in practice are difficult to deal with. Therefore, the research on TOTP problem for an aircraft slung-load system needs to be further explored, which is the focus of this article.