Space Navigator: a Tool for the Optimization of Collision Avoidance Maneuvers
The number of space objects will grow several times in a few years due to the planned launches of constellations of thousands microsatellites. It leads to a significant increase in the threat of satellite collisions. Spacecraft must undertake collision avoidance maneuvers to mitigate the risk. According to publicly available information, conjunction events are now manually handled by operators on the Earth. The manual maneuver planning requires qualified personnel and will be impractical for constellations of thousands satellites. In this paper we propose a new modular autonomous collision avoidance system called "Space Navigator". It is based on a novel maneuver optimization approach that combines domain knowledge with Reinforcement Learning methods.
Code (0)
등록된 구현이 없습니다.
Tasks
Collision Avoidancereinforcement-learningReinforcement LearningReinforcement Learning (RL)Similar Papers 제목 키워드 기반
Reward Function Optimization of a Deep Reinforcement Learning Collision Avoidance System
The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport ca…
Collision AvoidanceDeep Reinforcement Learningreinforcement-learningReinforcement Learning (RL)Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning
New methodologies will be needed to ensure the airspace remains safe and efficient as traffic densities rise to accommodate new unmanned operations. This paper explores how unmanned free-flight traffic may operate in den…
Collision AvoidanceDeep Reinforcement Learningreinforcement-learningReinforcement Learning+1"Why This Avoidance Maneuver?" Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation
Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system perceives a scenario and plans a maneuver. However, the causal logic be…
Collision AvoidanceImplicit Neural Field-Based Process Planning for Multi-Axis Manufacturing: Direct Control over Collision Avoidance and Toolpath Geometry
Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a post-processing step, leaving toolpath geometry uncontrolled during optimiz…
Collision AvoidanceDeep Neural Network Compression for Aircraft Collision Avoidance Systems
One approach to designing decision making logic for an aircraft collision avoidance system frames the problem as a Markov decision process and optimizes the system using dynamic programming. The resulting collision avoid…
Collision AvoidanceDecision MakingNeural Network Compression