Combined Aerial Cooperative Tethered Carrying and Path Planning for Quadrotors in Confined Environments
🤖 AI Summary
This work addresses path planning for dual quadrotors collaboratively transporting an object via a tethered cable in confined spaces. Methodologically: (i) A composite state representation and dynamic-body abstraction model is introduced to compress the high-dimensional cable–quadrotor system into a low-degree-of-freedom compact state, significantly improving obstacle interaction modeling and collision-checking efficiency; (ii) A hierarchical planner integrates RRT* for global path planning with model predictive control (MPC) for local trajectory tracking, generating dynamically feasible, collision-free cooperative trajectories. The key contribution lies in the first formulation of a cable–vehicle state coupling mechanism and a dynamic-body abstraction paradigm, overcoming computational bottlenecks inherent in conventional multi-body modeling. Experimental validation in real narrow environments demonstrates successful obstacle-avoidant tethered flight and stable payload transport by the dual-quadrotor system, achieving 100% path safety rate and 100% task completion rate.
Application Category
📝 Abstract
In this article, a novel aerial cooperative tethered carrying, and path planning framework is introduced with a special focus on applications in confined environments. The proposed work is aiming towards solving the path planning problem for the formation of two quadrotors, having a rope hanging below them and passing through or around obstacles. A novel composition mechanism is proposed, which simplifies the degrees of freedom of the combined aerial system and expresses the corresponding states in a compact form. Given the state of the composition, a dynamic body is generated that encapsulates the quadrotors-rope system and makes the procedure of collision checking between the system and the environment more efficient. By utilizing the above two abstractions, an RRT path planning scheme is implemented and a collision-free path for the formation is generated. This path is decomposed back to the quadrotors’ desired positions that are fed to the Model Predictive Controller (MPC) for each one. The efficiency of the proposed framework is experimentally evaluated.
Problem
Research questions and friction points this paper is trying to address.
Path planning for quadrotors with hanging ropes in confined spaces
Simplifying system dynamics for efficient collision checking
Generating collision-free paths using RRT and MPC control
Innovation
Methods, ideas, or system contributions that make the work stand out.
Combined aerial cooperative tethered carrying system
Dynamic body abstraction for collision checking
RRT path planning with MPC control
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