RINGO: Real-time Navigation with a Guiding Trajectory for Aerial Manipulators in Unknown Environments

TL;DR

RINGO presents a real-time, whole-body motion-planning framework for aerial manipulators operating in unknown environments. It leverages a pre-planned rotor trajectory as a guiding reference and optimizes the end-effector path using a shared $B$-spline representation, with the convex-hull property guaranteeing workspace containment. The approach combines workspace, yaw-rate, smoothness, and obstacle-avoidance costs into a gradient-based optimization, delivering collision-free and workspace-compatible trajectories without reducing the system to a multi-rotor-only model. Validation includes simulations and two autonomous experiments in unknown environments, demonstrating reduced conservatism and real-time performance compared with rotor-only planning.

Abstract

Motion planning for aerial manipulators in constrained environments has typically been limited to known environments or simplified to that of multi-rotors, which leads to poor adaptability and overly conservative trajectories. This paper presents RINGO: Real-time Navigation with a Guiding Trajectory, a novel planning framework that enables aerial manipulators to navigate unknown environments in real time. The proposed method simultaneously considers the positions of both the multi-rotor and the end-effector. A pre-obtained multi-rotor trajectory serves as a guiding reference, allowing the end-effector to generate a smooth, collision-free, and workspace-compatible trajectory. Leveraging the convex hull property of B-spline curves, we theoretically guarantee that the trajectory remains within the reachable workspace. To the best of our knowledge, this is the first work that enables real-time navigation of aerial manipulators in unknown environments. The simulation and experimental results show the effectiveness of the proposed method. The proposed method generates less conservative trajectories than approaches that consider only the multi-rotor.

Figures (15)

• Figure 1: Our proposed method is validated in a real-world environment. Experimental details are given in Sec. \ref{['sec:implementation_results']}.
• Figure 2: Illustration of the aerial manipulator and the defined coordinate frames.
• Figure 3: Illustration of the linear property of the B-spline curve.
• Figure 4: Illustration of the proposed guiding trajectory-based motion planning method.
• Figure 5: Initial trajectory for the end-effector.

Theorems & Definitions (1)

• Remark 1