RINGO: Real-time Navigation with a Guiding Trajectory for Aerial Manipulators in Unknown Environments
🤖 AI Summary
Aerial manipulators suffer from poor real-time navigation adaptability and overly conservative end-effector trajectories in unknown, constrained environments.
Method: We propose a coupled airframe-end-effector real-time trajectory planning framework. Dynamic environment modeling is performed online via point-cloud perception, and B-spline trajectories are optimized within a receding horizon. By jointly incorporating kinematic constraints and leveraging the convex hull property of B-splines, we theoretically guarantee that the end-effector trajectory remains collision-free and strictly confined within the reachable workspace.
Contribution/Results: This work presents the first end-to-end real-time navigation solution for aerial manipulators in unknown environments, achieving a balanced trade-off between safety and aggressiveness. Compared to airframe-only trajectory planning, our approach yields significantly more efficient and less conservative end-effector motion. Extensive simulations and physical experiments validate the algorithm’s real-time performance (<50 ms per frame) and robustness under dynamic, cluttered conditions.
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Real-time navigation for aerial manipulators in unknown environments
Simultaneous planning for multi-rotor and end-effector positions
Generating collision-free trajectories within reachable workspace
Innovation
Methods, ideas, or system contributions that make the work stand out.
Real-time navigation for aerial manipulators in unknown environments
Guiding trajectory ensures collision-free end-effector movement
B-spline curves guarantee workspace-compatible trajectories
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