What is it about?
In this paper, a kinodynamic inspection path planner called the Random Kinodynamic Inspection Tree algorithm is presented to perform in-close proximity full-coverage on-orbit inspection for the space structures under kinematic/dynamic motion constraints in deep space environments. The presented approach combines a novel coverage planning scheme with a kinodynamic motion planner to quickly and effectively solve the inspection path planning problem while at the same time handling both holonomic and non-holonomic constraints of the environment and the inspector robot. Our planner avoids the previous decoupled two steps method, which usually has been used to solve coverage planning problems, namely the Art Gallery and Traveling salesman problems, which are difficult or infeasible to be applied to a robot with differential constraints working in a high-dimensional environment. By contrast, our planner employs the Rapidly Exploring Random Tree algorithm as an asymptotically-optimal sampling-based technique in cooperation with a Linear Quadratic Minimum Time controller to generate an optimal and smooth inspection trajectory for any space structures, given complete knowledge of the structure and inspector’s dynamics. The algorithm guarantees probabilistic completeness.
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Why is it important?
Autonomous space robotics has been identified in the NASA Technology Roadmaps as one of the essential technologies for the future of space exploration. Inspection, as one of the key elements of proximity operations, would make a significant breakthrough in on-orbit servicing and, therefore, space exploration missions. Therefore, we have chosen to work on the autonomous on-orbit inspection of large space structures, which is a new challenging area and has received very little attention in the scientific community thus far.
Read the Original
This page is a summary of: Kinodynamic on-orbit inspection path planning for full-coverage inspection in close proximity of space structures, Acta Astronautica, September 2022, Elsevier, DOI: 10.1016/j.actaastro.2022.04.038.
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