Human-Robot Collaboration via Deep Reinforcement Learning of Real-World Interactions

2019-12-02 · Jonas Tjomsland, Ali Shafti, A. Aldo Faisal

We present a robotic setup for real-world testing and evaluation of human-robot and human-human collaborative learning. Leveraging the sample-efficiency of the Soft Actor-Critic algorithm, we have implemented a robotic platform able to learn a non-trivial collaborative task with a human partner, without pre-training in simulation, and using only 30 minutes of real-world interactions. This enables us to study Human-Robot and Human-Human collaborative learning through real-world interactions. We present preliminary results, showing that state-of-the-art deep learning methods can take human-robot collaborative learning a step closer to that of humans interacting with each other.

📄 PDF Abstract BibTeX arXiv:1912.01715

Code (0)

등록된 구현이 없습니다.

Tasks

Deep Reinforcement Learningreinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Real-World Human-Robot Collaborative Reinforcement Learning

2020-03-02 · Ali Shafti, Jonas Tjomsland, William Dudley, A. Aldo Faisal

The intuitive collaboration of humans and intelligent robots (embodied AI) in the real-world is an essential objective for many desirable applications of robotics. Whilst there is much research regarding explicit communi…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

ContactRL: Safe Reinforcement Learning based Motion Planning for Contact based Human Robot Collaboration

2025-12-03 · Sundas Rafat Mulkana, Ronyu Yu, Tanaya Guha, Emma Li arxiv

In collaborative human-robot tasks, safety requires not only avoiding collisions but also ensuring safe, intentional physical contact. We present ContactRL, a reinforcement learning (RL) based framework that directly inc…

Reinforcement Learning Motion Planning

A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors

2023-02-25 · Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen 외

Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment. Safe Robot RL (SRRL) is a crucial step towards achieving hum…

reinforcement-learning Reinforcement Learning (RL)Safe Exploration

Learning Human-Humanoid Coordination for Collaborative Object Carrying

2025-10-16 · Yushi Du, Yixuan Li, Baoxiong Jia, Yutang Lin 외 arxiv

Human-humanoid collaboration shows significant promise for applications in healthcare, domestic assistance, and manufacturing. While compliant robot-human collaboration has been extensively developed for robotic arms, en…

Reinforcement Learning Trajectory Planning

Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees

2026-04-16 · Jakob Thumm, Marian Frei, Tianle Ni, Matthias Althoff 외 arxiv

We propose a framework for vision-based human pose estimation and motion prediction that gives conformal prediction guarantees for certifiably safe human-robot collaboration. Our framework combines aleatoric uncertainty …

Pose Estimation