Research/ PLANETARY ROBOTICS
Simulation for Planetary Robotic Perception and Autonomy: A Concise Survey of Recent Capabilities and Gaps
Hoyun Kim, Giseop Kim
Perception & State EstimationOpenAlex topic: Robotics and Sensor-Based Localization · Simulation, Digital Twins & BenchmarksOpenAlex keyword: synthetic data generation · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics
arXivcs.ROOpenAlexRobotics and Sensor-Based Localization · Reinforcement Learning in Robotics · Planetary Science and Exploration
Planetary robotics is an important enabler of scientific exploration in environments where direct human-in-the-loop operation is costly, hazardous, or infeasible. However, developing and validating planetary robotic systems remains difficult because representative field testing is expensive, limited, and often unrepeatable under mission-relevant conditions. In this setting, simulation serves as a central tool for perception and autonomy research, synthetic data generation, system integration, and pre-deployment evaluation. Despite its importance, the literature on planetary robotics simulation remains dispersed across different simulation engines, implementations, and application settings. This paper surveys simulation works for planetary robotic perception and autonomy across four practical axes: Openness and Availability, Scenario and Platform Coverage, Sensor and Perception Support, and Environmental and Operational Realism. The surveyed simulation works report visual or physical fidelity and support perception-oriented workflows. They also indicate uneven public availability, rover-centered coverage, partial support for specialized sensing modalities, and uneven reporting of operational constraints such as onboard computation, energy, and communication restrictions.
Comments: 8 pages, 5 figures, 3 tables. Accepted for publication at the 2026 International Conference on Space Robotics (iSpaRo)