Overview
New space applications include topics like space debris removal, docking, in-orbit servicing, or close proximity operations. Such operations have in common that satellites and probes operate in close vicinity to each other and a high level of automation is required. At the same time there is a high demand for safe maneuvers in order to avoid collisions. Related settings also occur in automated production lines with manipulators and mobile robotic platforms. Depending on the task to be performed, the maneuverability requirements can range from low to high. Ensuring collision-freenes is a challenge especially in close proximity operations as the precise geometry of the involved probes needs to be considered. We focus on trajectory optimization aspects and employ the following techniques:
- Reinforcement Learning (RL) combining optimal control and waypoint generation in the presence of obstacles
- a bilevel dynamic programming approach for obstacle avoidance
- optimal control methods
- collision detection algorithms
Application scenarios:
- docking maneuvers to a tumbling target for space debris removal
- close proximity operations for satellite inspection, in-orbit servicing, and satellite protection
The methods are implemented and tested on our mobile robots in a lab environment. We use the robot operating system ROS2 and the Unreal Engine for visualization.