# Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs

arXiv: https://arxiv.org/abs/2011.08811 · HTML: https://mlsanity.com/paper/2011.08811/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Nov 2020.

## Built on by (most cited first, 16 of 16)

- [DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality](https://mlsanity.com/paper/2210.13702/) (2022)
- [DribbleBot: Dynamic Legged Manipulation in the Wild](https://mlsanity.com/paper/2304.01159/) (2023)
- [Legs as Manipulator: Pushing Quadrupedal Agility Beyond Locomotion](https://mlsanity.com/paper/2303.11330/) (2023)
- [Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger](https://mlsanity.com/paper/2108.09779/) (2021)
- [Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot](https://mlsanity.com/paper/2208.01160/) (2022)
- [Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg](https://mlsanity.com/paper/2402.10837/) (2024)
- [Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers](https://mlsanity.com/paper/2405.12424/) (2024)
- [Learning Multi-Agent Loco-Manipulation for Long-Horizon Quadrupedal Pushing](https://mlsanity.com/paper/2411.07104/) (2024)
- [On the Feasibility of Learning Finger-gaiting In-hand Manipulation with Intrinsic Sensing](https://mlsanity.com/paper/2109.12720/) (2021)
- [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)
- [Simultaneous Contact-Rich Grasping and Locomotion via Distributed Optimization Enabling Free-Climbing for Multi-Limbed Robots](https://mlsanity.com/paper/2207.01418/) (2022)
- [Quadruped Locomotion on Non-Rigid Terrain using Reinforcement Learning](https://mlsanity.com/paper/2107.02955/) (2021)
- [CAIMAN: Causal Action Influence Detection for Sample-efficient Loco-manipulation](https://mlsanity.com/paper/2502.00835/) (2025)
- [Affordance-Based Hierarchical Reinforcement Learning for Quadruped Pedipulation](https://mlsanity.com/paper/2606.07506/) (2026)
- [Continual-RL for Generalization in Autonomous Racing on the RoboRacer Platform](https://mlsanity.com/paper/2607.24320/) (2026)

## Abstract (arXiv)

Quadrupedal robots are skillful at locomotion tasks while lacking manipulation skills, not to mention dexterous manipulation abilities. Inspired by the animal behavior and the duality between multi-legged locomotion and multi-fingered manipulation, we showcase a circus ball challenge on a quadrupedal robot, ANYmal. We employ a model-free reinforcement learning approach to train a deep policy that enables the robot to balance and manipulate a light-weight ball robustly using its limbs without any contact measurement sensor. The policy is trained in the simulation, in which we randomize many physical properties with additive noise and inject random disturbance force during manipulation, and achieves zero-shot deployment on the real robot without any adjustment. In the hardware experiments, dynamic performance is achieved with a maximum rotation speed of 15 deg/s, and robust recovery is showcased under external poking. To our best knowledge, it is the first work that demonstrates the dexterous dynamic manipulation on a real quadrupedal robot.