# Legs as Manipulator: Pushing Quadrupedal Agility Beyond Locomotion

arXiv: https://arxiv.org/abs/2303.11330 · HTML: https://mlsanity.com/paper/2303.11330/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 36 references that are in the map.
- First posted on arXiv 20 Mar 2023.

## Builds on (most cited first, 22 of 22)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [Learning Quadrupedal Locomotion over Challenging Terrain](https://mlsanity.com/paper/2010.11251/) (2020)
- [Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning](https://mlsanity.com/paper/2109.11978/) (2021)
- [RMA: Rapid Motor Adaptation for Legged Robots](https://mlsanity.com/paper/2107.04034/) (2021)
- [Learning robust perceptive locomotion for quadrupedal robots in the wild](https://mlsanity.com/paper/2201.08117/) (2022)
- [Learning Agile Robotic Locomotion Skills by Imitating Animals](https://mlsanity.com/paper/2004.00784/) (2020)
- [Legged Locomotion in Challenging Terrains using Egocentric Vision](https://mlsanity.com/paper/2211.07638/) (2022)
- [Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion](https://mlsanity.com/paper/2210.10044/) (2022)
- [Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots](https://mlsanity.com/paper/2103.14295/) (2021)
- [RRL: Resnet as representation for Reinforcement Learning](https://mlsanity.com/paper/2107.03380/) (2021)
- [Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion](https://mlsanity.com/paper/2202.05481/) (2022)
- [Minimizing Energy Consumption Leads to the Emergence of Gaits in Legged Robots](https://mlsanity.com/paper/2111.01674/) (2021)
- [Fast and Efficient Locomotion via Learned Gait Transitions](https://mlsanity.com/paper/2104.04644/) (2021)
- [Adapting Rapid Motor Adaptation for Bipedal Robots](https://mlsanity.com/paper/2205.15299/) (2022)
- [Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization](https://mlsanity.com/paper/2111.07999/) (2021)
- [Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real](https://mlsanity.com/paper/1908.05224/) (2019)
- [Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot](https://mlsanity.com/paper/2208.01160/) (2022)
- [Cross-Domain Transfer via Semantic Skill Imitation](https://mlsanity.com/paper/2212.07407/) (2022)
- [Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs](https://mlsanity.com/paper/2011.08811/) (2020)
- [Dynamic Legged Manipulation of a Ball Through Multi-Contact Optimization](https://mlsanity.com/paper/2008.00191/) (2020)

## Built on by (most cited first, 30 of 39)

- [RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation](https://mlsanity.com/paper/2311.01455/) (2023)
- [Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes](https://mlsanity.com/paper/2408.03539/) (2024)
- [Extreme Parkour with Legged Robots](https://mlsanity.com/paper/2309.14341/) (2023)
- [Robot Parkour Learning](https://mlsanity.com/paper/2309.05665/) (2023)
- [Open-TeleVision: Teleoperation with Immersive Active Visual Feedback](https://mlsanity.com/paper/2407.01512/) (2024)
- [Expressive Whole-Body Control for Humanoid Robots](https://mlsanity.com/paper/2402.16796/) (2024)
- [Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning](https://mlsanity.com/paper/2304.13653/) (2023)
- [Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control](https://mlsanity.com/paper/2401.16889/) (2024)
- [Visual Whole-Body Control for Legged Loco-Manipulation](https://mlsanity.com/paper/2403.16967/) (2024)
- [Mobile-TeleVision: Predictive Motion Priors for Humanoid Whole-Body Control](https://mlsanity.com/paper/2412.07773/) (2024)
- [AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control](https://mlsanity.com/paper/2505.03738/) (2025)
- [Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion](https://mlsanity.com/paper/2308.12517/) (2023)
- [Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response](https://mlsanity.com/paper/2312.11460/) (2023)
- [BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities](https://mlsanity.com/paper/2503.05652/) (2025)
- [Learning Smooth Humanoid Locomotion through Lipschitz-Constrained Policies](https://mlsanity.com/paper/2410.11825/) (2024)
- [Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg](https://mlsanity.com/paper/2402.10837/) (2024)
- [Leveraging Symmetry in RL-based Legged Locomotion Control](https://mlsanity.com/paper/2403.17320/) (2024)
- [Learning Visual Quadrupedal Loco-Manipulation from Demonstrations](https://mlsanity.com/paper/2403.20328/) (2024)
- [Generalized Animal Imitator: Agile Locomotion with Versatile Motion Prior](https://mlsanity.com/paper/2310.01408/) (2023)
- [Learning Multi-Agent Loco-Manipulation for Long-Horizon Quadrupedal Pushing](https://mlsanity.com/paper/2411.07104/) (2024)
- [Learning Whole-Body Loco-Manipulation for Omni-Directional Task Space Pose Tracking with a Wheeled-Quadrupedal-Manipulator](https://mlsanity.com/paper/2412.03012/) (2024)
- [SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending](https://mlsanity.com/paper/2506.09366/) (2025)
- [Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining](https://mlsanity.com/paper/2506.16475/) (2025)
- [PA-LOCO: Learning Perturbation-Adaptive Locomotion for Quadruped Robots](https://mlsanity.com/paper/2407.04224/) (2024)
- [Helpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models](https://mlsanity.com/paper/2410.00231/) (2024)
- [Whole-body End-Effector Pose Tracking](https://mlsanity.com/paper/2409.16048/) (2024)
- [Adaptive Energy Regularization for Autonomous Gait Transition and Energy-Efficient Quadruped Locomotion](https://mlsanity.com/paper/2403.20001/) (2024)
- [Versatile Loco-Manipulation through Flexible Interlimb Coordination](https://mlsanity.com/paper/2506.07876/) (2025)
- [HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation](https://mlsanity.com/paper/2407.06584/) (2024)
- [Bipedalism for Quadrupedal Robots: Versatile Loco-Manipulation through Risk-Adaptive Reinforcement Learning](https://mlsanity.com/paper/2507.20382/) (2025)

## Abstract (arXiv)

Locomotion has seen dramatic progress for walking or running across challenging terrains. However, robotic quadrupeds are still far behind their biological counterparts, such as dogs, which display a variety of agile skills and can use the legs beyond locomotion to perform several basic manipulation tasks like interacting with objects and climbing. In this paper, we take a step towards bridging this gap by training quadruped robots not only to walk but also to use the front legs to climb walls, press buttons, and perform object interaction in the real world. To handle this challenging optimization, we decouple the skill learning broadly into locomotion, which involves anything that involves movement whether via walking or climbing a wall, and manipulation, which involves using one leg to interact while balancing on the other three legs. These skills are trained in simulation using curriculum and transferred to the real world using our proposed sim2real variant that builds upon recent locomotion success. Finally, we combine these skills into a robust long-term plan by learning a behavior tree that encodes a high-level task hierarchy from one clean expert demonstration. We evaluate our method in both simulation and real-world showing successful executions of both short as well as long-range tasks and how robustness helps confront external perturbations. Videos at https://robot-skills.github.io