Orbit-Planner: Towards Latent World Models for On-Orbit Obstacle Avoidance of Satellite Agents
On the map: World models → World models for navigation
Abstract (arXiv)
Satellite agents for on-orbit navigation tasks need to predict collision risks using limited onboard observations. However, conventional planners often rely on predefined maps and fixed environmental assumptions, limiting their adaptability in dynamic on-orbit scenarios. In this paper, we propose Orbit-Planner, a two-stage latent world model for on-orbit obstacle avoidance. Orbit-Planner learns action-conditioned spacecraft dynamics to perform future-state rollouts in latent space, and introduces a Physics Probe to decode physical state changes from imagined latent trajectories. Experiments demonstrate that Orbit-Planner can perform long-horizon latent rollouts and recover physical states from imagined trajectories. In closed-loop obstacle-avoidance navigation in Isaac Sim, it attains a success rate of 91.7%. Code is available at https://github.com/ZhijianLi2003/Orbit_Planner.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in World models for navigation, one of 11 directions in World models. Builds on 7 of its 9 references that are in the map. First posted on arXiv 17 Aug 2026.
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7 of 9 references.
References · 7
- 2022Scalable Diffusion Models with Transformerscited by 6,054
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
- 2023TD-MPC2: Scalable, Robust World Models for Continuous Controlcited by 512
- 2026LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixelscited by 273
- 2015Model Predictive Path Integral Control using Covariance Variable Importance Samplingcited by 124
- 2026SkyJEPA: Learning Long-Horizon World Models for Zero-Shot Sim-to-Real Control of Quadrotorscited by 9
- 2025Space Robotics Bench: Robot Learning Beyond Earthcited by 4
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- 2026Reward-Free Continual Adaptation for Resilient Space Robots
- 2024LaPlaSS: Latent Space Planning for Stochastic Systems
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