mlsanityData to 14 Oct 2026

Ask1: Development and Reinforcement Learning-Based Control of a Custom Quadruped Robot

arXiv 2412.08019 ↗First posted 11 Dec 2024cs.RO cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

In this work, we present the design, development, and experimental validation of a custom-built quadruped robot, Ask1. The Ask1 robot shares similar morphology with the Unitree Go1, but features custom hardware components and a different control architecture. We transfer and extend previous reinforcement learning (RL)-based control methods to the Ask1 robot, demonstrating the applicability of our approach in real-world scenarios. By eliminating the need for Adversarial Motion Priors (AMP) and reference trajectories, we introduce a novel reward function to guide the robot's motion style. We demonstrate the generalization capability of the proposed RL algorithm by training it on both the Go1 and Ask1 robots. Simulation and real-world experiments validate the effectiveness of this method, showing that Ask1, like the Go1, is capable of navigating various rugged terrains.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 13 of its 19 references that are in the map. First posted on arXiv 11 Dec 2024.

Builds on

13 of 19 references.

References · 13

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 604
  3. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  4. 2021RMA: Rapid Motor Adaptation for Legged Robotscited by 508
  5. 2019Learning agile and dynamic motor skills for legged robotscited by 504
  6. 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 382
  7. 2017Asymmetric Actor Critic for Image-Based Robot Learningcited by 238
  8. 2022Rapid Locomotion via Reinforcement Learningcited by 168
  9. 2022Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behaviorcited by 138
  10. 2022Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotioncited by 88
  11. 2020Representation-Free Model Predictive Control for Dynamic Motions in Quadrupedscited by 13
  12. 2020Efficient Multi-Contact Pattern Generation with Sequential Convex Approximations of the Centroidal Dynamicscited by 8
1 more
  1. 2022BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planningcited by 8

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  1. 2024Reinforcement Learning For Quadrupedal Locomotion: Current Advancements And Future Perspectives
  2. 2026Towards Torque-Driven Reinforcement Learning for Quadruped Locomotion
  3. 2025Acrobotics: A Generalist Approach to Quadrupedal Robots' Parkour
  4. 2025A Framework for Deploying Learning-based Quadruped Loco-Manipulation ↗
  5. 2023A Real-World Quadrupedal Locomotion Benchmark for Offline Reinforcement Learning
  6. 2025Training Directional Locomotion for Quadrupedal Low-Cost Robotic Systems via Deep Reinforcement Learning
  7. 2025Quadruped Robot Simulation Using Deep Reinforcement Learning -- A step towards locomotion policy
  8. 2025GRoQ-LoCO: Generalist and Robot-agnostic Quadruped Locomotion Control using Offline Datasets