Papers for

space mission operators

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Robots safely push objects in space using human guidance

Multi-Agent Transportation of Free-Flyers in Microgravity Via Pushing Interaction Under Human-in-the-Loop Control

Abstract: We propose a safety-critical framework for the cooperative transportation of passive targets in microgravity, where a team of chaser robots acts through unilateral pushing contacts to track a human-provided desired twist while ensuring safe target motion. The pushing-only nature of the interaction introduces sparse, configuration-dependent actuation constraints requiring chasers to physically relocate on the target body when the desired pushing allocation changes. To address these challenges, we formulate a delay-aware feedback control architecture leveraging Control Lyapunov Function (CLF) and Control Barrier Function (CBF) constraints within a mixed-integer thrust allocation program to enforce stability and safety of the target, respectively. The proposed framework enables reference tracking while guaranteeing obstacle avoidance with a circular obstacle despite intermittent control authority, providing a foundation for human-supervised cooperative transportation of free-flyers in space environments. The proposed framework is validated through Gazebo simulations.

Mon 21 SeptRobotics
The gist
Moving objects in space without gravity is tricky because robots can only push on one side and need to work together carefully. The authors designed a system where several robots push an object to move it as a human wants while making sure it doesn't crash into obstacles. Their system uses special math rules to keep the object stable and safe, even if the robots have to wait before acting. They tested their approach in computer simulations to show it works.
Open 2609.24376v1

Autonomous spacecraft maneuver planning improves collision avoidance under uncertainty

Chance-Constrained Belief-Space Maneuver Planning for Autonomous Collision Avoidance Under Uncertainty

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.

Fri 11 SeptRoboticsArtificial Intelligence
The gist
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.
Open 2609.13428v1