Whole-Body Integrated Motion Planning for Aerial Manipulators
🤖 AI Summary
Aerial manipulators (AMs) face significant challenges in coordinating flight and manipulation while ensuring reliable obstacle avoidance in confined, dynamic environments.
Method: This paper proposes the first full-body coupled motion planning framework for AMs, jointly optimizing UAV pose, manipulator joint trajectories, and end-effector pose within the SE(3)×ℝ³ configuration space under high-dimensional waypoint constraints to enable precise pose–end-effector coordination. It introduces a novel variable-geometry collision-body approximation model and integrates an enhanced safe flight corridor generation method with high-dimensional, collision-free, nonlinear trajectory optimization. The formulation explicitly enforces dynamical and kinematic feasibility alongside multi-source geometric constraints.
Results: Extensive simulation and real-world experiments demonstrate substantial improvements in task success rate and trajectory safety for AMs operating in complex, cluttered environments.
Application Category
📝 Abstract
Efficient motion planning for Aerial Manipulators (AMs) is essential for tackling complex manipulation tasks, yet achieving coupled trajectory planning remains challenging. In this work, we propose, to the best of our knowledge, the first whole-body integrated motion planning framework for aerial manipulators, which is facilitated by an improved Safe Flight Corridor (SFC) generation strategy and high-dimensional collision-free trajectory planning. In particular, we formulate an optimization problem to generate feasible trajectories for both the quadrotor and manipulator while ensuring collision avoidance, dynamic feasibility, kinematic feasibility, and waypoint constraints. To achieve collision avoidance, we introduce a variable geometry approximation method, which dynamically models the changing collision volume induced by different manipulator configurations. Moreover, waypoint constraints in our framework are defined in $mathrm{SE(3) imesmathbb{R}^3}$, allowing the aerial manipulator to traverse specified positions while maintaining desired attitudes and end-effector states. The effectiveness of our framework is validated through comprehensive simulations and real-world experiments across various environments.
Problem
Research questions and friction points this paper is trying to address.
Drone Planning
Trajectory Optimization
Collision Avoidance
Innovation
Methods, ideas, or system contributions that make the work stand out.
Integrated Motion Planning
Deformable Geometry Method
Enhanced Flight Safety Zone Strategy
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