Autonomous spacecraft maneuver planning improves collision avoidance under uncertainty
Chance-Constrained Belief-Space Maneuver Planning for Autonomous Collision Avoidance Under Uncertainty
RoboticsArtificial Intelligence
Summary
Spacecraft operating in low Earth orbit face more frequent chances of colliding with objects. The authors created a planning method that helps decide when a spacecraft should move to avoid collisions based on how much is known about the uncertain positions of nearby objects. Their method waits for better tracking data when possible, but maneuvers if the risk becomes too high. Tests on real historical data showed this approach could safely reduce unnecessary maneuvers while maintaining collision safety.
What this means in practice
- •For space mission operators: Make informed decisions about collision avoidance maneuvers by balancing risk and information quality in real-time orbit tracking.
- •For satellite operators: Reduce unnecessary spacecraft maneuvers by using chance-constrained planning that adapts to measurement accuracy and tracking frequency.
Authors
Grace Ra Kim, Duncan Eddy, Mykel J. Kochenderfer
Abstract
Increasing conjunction frequency in low Earth orbit places growing pressure on spacecraft operators to determine not only whether an encounter requires mitigation, but whether sufficient information is available to commit to a maneuver. This work formulates this information-action tradeoff as a belief-space planning problem for conjunctions between a maneuverable spacecraft and an unmaneuverable secondary object. The planner represents the uncertain orbital states as Gaussian beliefs and uses a chance-constrained belief-space Monte Carlo tree search framework to reason over possible future tracking updates before time of closest approach (TCA). A terminal chance constraint limits the probability of reaching TCA above a prescribed collision-risk threshold, allowing the planner to wait for informative tracking while intervening when deferral becomes too risky. We evaluate the approach on eight historical conjunctions from NASA's Conjunction Assessment Risk Analysis dataset. By varying the secondary-object measurement quality and tracking cadence, we generate a total of 96 distinct evaluation scenarios. Across the evaluated conditions, the planner reaches TCA without maneuvering in approximately 40% of episodes while maintaining no terminal collision-risk violations. In contrast, fixed-time rule-based maneuver policies resolve more encounters without maneuvering when intervention is deferred closer to TCA, but at the expense of increasing terminal risk violations. The fraction of episodes reaching TCA without maneuvering depends strongly on tracking quality and measurement cadence, ranging from 76% under accurate, frequent measurements to approximately 18%-20% under the poorest tracking conditions. These results show that tracking quality and frequency are not only inputs to collision-risk estimation: they can determine when intervention becomes necessary.