mlsanityData to 14 Oct 2026

Reinforcement Learning for Docking Maneuvers with Prescribed Performance

arXiv 2402.08306 ↗First posted 13 Feb 2024math.OCcited by 0

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

We propose a two-component data-driven controller to safely perform docking maneuvers for satellites. Reinforcement Learning is used to deduce an optimal control policy based on measurement data. To safeguard the learning phase, an additional feedback law is implemented in the control unit, which guarantees the evolution of the system within predefined performance bounds. We define safe and safety-critical areas to train the feedback controller based on actual measurements. To avoid chattering, a dwell-time activation scheme is implemented. We provide numerical evidence for the performance of the proposed controller for a satellite docking maneuver with collision avoidance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 12 of its 24 references that are in the map. First posted on arXiv 13 Feb 2024.

Builds on

12 of 24 references.

References · 12

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2015Trust Region Policy Optimizationcited by 2,580
  3. 2022Funnel-based Reward Shaping for Signal Temporal Logic Tasks in Reinforcement Learningcited by 8
  4. 2022Funnel Control Under Hard and Soft Output Constraints (extended version)cited by 2
  5. 2013Optimal Rendezvous Path Planning to an Uncontrolled Tumbling Targetcited by 1
  6. 2020Funnel control of nonlinear systemscited by 1
  7. 2020Tracking control for underactuated non-minimum phase multibody systemscited by 1
  8. 2023Robust Funnel Model Predictive Control for output tracking with prescribed performancecited by 1
  9. 2023Sampled-data funnel control and its use for safe continual learningcited by 1
  10. 2023Safe continual learning in model predictive control with prescribed bounds on the tracking errorcited by 1
  11. 2023Experimental validation for the combination of funnel control with a feedforward control strategycited by 1
  12. 2023Safe data-driven reference tracking with prescribed performancecited by 1

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  1. 2024Neural-based Control for CubeSat Docking Maneuvers
  2. 2026Imitation learning-based spacecraft rendezvous and docking method with Expert Demonstration
  3. 2025Coupled Rendezvous and Docking Maneuver control of satellite using Reinforcement learning-based Adaptive Fixed-Time Sliding Mode Controller ↗
  4. 2026Meta-Reinforcement Learning for Robust and Non-greedy Control Barrier Functions in Spacecraft Proximity Operations
  5. 2026Learning Safety-Guaranteed, Non-Greedy Control Barrier Functions Using Reinforcement Learning
  6. 2026SCoCaT: Success Conditioned Constrained Reinforcement Learning for Spacecraft Docking
  7. 2026From Orbit Matching to Docking: A Hierarchical Reinforcement-Learning Approach to Multiphase Rendezvous Trajectory Design
  8. 2025Reinforcement Learning based 6-DoF Maneuvers for Microgravity Intravehicular Docking: A Simulation Study with Int-Ball2 in ISS-JEM