# Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots

arXiv: https://arxiv.org/abs/2307.10079 · HTML: https://mlsanity.com/paper/2307.10079/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2023.

## Built on by (most cited first, 20 of 20)

- [Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI](https://mlsanity.com/paper/2407.06886/) (2024)
- [RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulation](https://mlsanity.com/paper/2402.15487/) (2024)
- [Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg](https://mlsanity.com/paper/2402.10837/) (2024)
- [Identifying Terrain Physical Parameters from Vision -- Towards Physical-Parameter-Aware Locomotion and Navigation](https://mlsanity.com/paper/2408.16567/) (2024)
- [DROID-SLAM in the Wild](https://mlsanity.com/paper/2603.19076/) (2026)
- [Whole-body End-Effector Pose Tracking](https://mlsanity.com/paper/2409.16048/) (2024)
- [DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learning](https://mlsanity.com/paper/2409.19709/) (2024)
- [Learning Adaptive Hydrodynamic Models Using Neural ODEs in Complex Conditions](https://mlsanity.com/paper/2410.00490/) (2024)
- [Disturbance-Aware Adaptive Compensation in Hybrid Force-Position Locomotion Policy for Legged Robots](https://mlsanity.com/paper/2506.00472/) (2025)
- [Embodied Image Quality Assessment for Robotic Intelligence](https://mlsanity.com/paper/2412.18774/) (2024)
- [Olympus: A Jumping Quadruped for Planetary Exploration Utilizing Reinforcement Learning for In-Flight Attitude Control](https://mlsanity.com/paper/2503.03574/) (2025)
- [Agile and versatile bipedal robot tracking control through reinforcement learning](https://mlsanity.com/paper/2404.08246/) (2024)
- [QuadWBG: Generalizable Quadrupedal Whole-Body Grasping](https://mlsanity.com/paper/2411.06782/) (2024)
- [Towards Quadrupedal Jumping and Walking for Dynamic Locomotion using Reinforcement Learning](https://mlsanity.com/paper/2510.24584/) (2025)
- [Path Planning and Reinforcement Learning-Driven Control of On-Orbit Free-Flying Multi-Arm Robots](https://mlsanity.com/paper/2603.23182/) (2026)
- [CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments](https://mlsanity.com/paper/2505.06483/) (2025)
- [Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robots](https://mlsanity.com/paper/2508.06538/) (2025)
- [Towards Low-Gravity Planetary Exploration using Reinforcement Learning for Walking, Jumping, and In-flight Attitude Control](https://mlsanity.com/paper/2605.24643/) (2026)
- [Affordance-Based Hierarchical Reinforcement Learning for Quadruped Pedipulation](https://mlsanity.com/paper/2606.07506/) (2026)
- [CLoSeR: Closing the Loop for Long-Context Streaming Reconstruction](https://mlsanity.com/paper/2610.01927/) (2026)

## Abstract (arXiv)

The interest in exploring planetary bodies for scientific investigation and in-situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots' inability to traverse steep slopes, unstructured terrain, and loose soil. Additionally, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficient locomotion controller, a mapping pipeline for online and post-mission visualization, instance segmentation to highlight scientific targets, and scientific instruments for remote and in-situ investigation. Furthermore, we integrated a robotic arm on one of the robots to enable high-precision measurements. Legged robots can swiftly navigate representative terrains, such as granular slopes beyond 25 degrees, loose soil, and unstructured terrain, highlighting their advantages compared to wheeled rover systems. We successfully verified the approach in analog deployments at the BeyondGravity ExoMars rover testbed, in a quarry in Switzerland, and at the Space Resources Challenge in Luxembourg. Our results show that a team of legged robots with advanced locomotion, perception, and measurement skills, as well as task-level autonomy, can conduct successful, effective missions in a short time. Our approach enables the scientific exploration of planetary target sites that are currently out of human and robotic reach.