Multi-Point Bounce Trajectory Planning on the Complex Surface of an Asteroid for Resource Exploitation

Asteroid exploration is a hot topic in current deep space exploration. Deploying a rover on the surface of an asteroid for reconnaissance is an important means to enhance the scientific return of exploration missions. Bouncing mobility, with its advantage of high maneuverability in weak gravity environments, is an effective surface mobility method. Bounce trajectory planning plays a key role in achieving effective bouncing mobility. This paper focuses on bounce trajectory planning for a rover on the irregular surface of an asteroid in the context of surface reconnaissance exploration. Firstly, based on the concept of dimensionality reduction, the three-dimensional complex shape of the asteroid is mapped to a two-dimensional height map using longitude and latitude. Then, a single-hop model is established for the rover's known starting and target points. Based on the two-dimensional map of the asteroid and the rover's single-hop model, the reachable range of a single hop is analyzed. An A* algorithm is combined to propose a single-hop-based bounce trajectory planning method. Next, to fully utilize the energy of the rover's initial jump and maximize its reachable distance in a single hop, a multi-hop model is established for the rover's known starting and target points. The reachable range of multiple hops is also analyzed, and a multi-hop-based bounce trajectory planning method is proposed. Finally, a comparative analysis is conducted between the single-hop-based and multi-hop-based trajectory planning methods. The impact of asteroid surface parameters on the rover's bouncing capability is evaluated to guide the deployment and design of asteroid exploration missions.

 

Acknowledgments

The authors acknowledge support from Young elite scientist sponsorship program by CAST (No. YESS20210296), the Beijing Institute of Technology Research Fund Program for Young Scholars (XSQD-202101012), Beijing Institute of Technology Research Fund Program for Innovative Talents (No. 2022CX01008).