A Short Survey on Recent State-of-the-Art Methods for Optimal Path Planning for Small On-Orbit Space Robots
Title: A Short Survey on Recent State-of-the-Art Methods for Optimal Path Planning for Small On-Orbit Space Robots
Authors: Jonathan Arreola (Cranfield University); Saurabh Upadhyay (Cranfield University);
Year: 2022
Citation: Arreola, J., Upadhyay, S., (2022). A Short Survey on Recent State-of-the-Art Methods for Optimal Path Planning for Small On-Orbit Space Robots. UKRAS22 Conference “Robotics for Unconstrained Environments” Proceedings, 36-37. doi: 10.31256/Du2Je8G
Abstract:
Abstract—Optimal path planning in the presence of multiple kinodynamic constraints and limited onboard computation power is a key challenge for small on-orbit space robots. This work surveys parameterized function and machine-learning based path planning approaches based on number of constraints solved and computation complexity. Limitations of the existing
approaches and potential directions are discussed.