mlsanityData to 7 Oct 2026

Know your limits! Optimize the robot's behavior through self-awareness

arXiv 2409.10308 ↗First posted 16 Sep 2024cs.RO cs.AIcited by 0

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Abstract (arXiv)

As humanoid robots transition from labs to real-world environments, it is essential to democratize robot control for non-expert users. Recent human-robot imitation algorithms focus on following a reference human motion with high precision, but they are susceptible to the quality of the reference motion and require the human operator to simplify its movements to match the robot's capabilities. Instead, we consider that the robot should understand and adapt the reference motion to its own abilities, facilitating the operator's task. For that, we introduce a deep-learning model that anticipates the robot's performance when imitating a given reference. Then, our system can generate multiple references given a high-level task command, assign a score to each of them, and select the best reference to achieve the desired robot behavior. Our Self-AWare model (SAW) ranks potential robot behaviors based on various criteria, such as fall likelihood, adherence to the reference motion, and smoothness. We integrate advanced motion generation, robot control, and SAW in one unique system, ensuring optimal robot behavior for any task command. For instance, SAW can anticipate falls with 99.29% accuracy. For more information check our project page: https://evm7.github.io/Self-AWare

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 23 of its 41 references that are in the map. First posted on arXiv 16 Sep 2024.

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23 of 41 references.

References · 23

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  12. 2023Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learningcited by 111
11 more
  1. 2022Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotioncited by 98
  2. 2021Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robotscited by 95
  3. 2021Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulationcited by 59
  4. 2021Cross-Domain Imitation Learning via Optimal Transportcited by 49
  5. 2024WoCoCo: Learning Whole-Body Humanoid Control with Sequential Contactscited by 49
  6. 2019Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learningcited by 30
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  10. 2023Fall Prediction for Bipedal Robots: The Standing Phasecited by 3
  11. 2018A Control Architecture with Online Predictive Planning for Position and Torque Controlled Walking of Humanoid Robotscited by 2

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