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As robots become ubiquitous in the workforce, it is essential that human-robot collaboration be both intuitive and adaptive. A robot's quality improves based on its ability to explicitly reason about the time-varying (i.e. learning curves)…

Robotics · Computer Science 2020-07-10 Ruisen Liu , Manisha Natarajan , Matthew Gombolay

Humanoid robotics has strong potential to transform daily service and caregiving applications. Although recent advances in general motion tracking within physics engines (GMT) have enabled virtual characters and humanoid robots to reproduce…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuto Shibata , Kashu Yamazaki , Lalit Jayanti , Yoshimitsu Aoki , Mariko Isogawa , Katerina Fragkiadaki

Human-robot collaboration (HRC) is an emerging trend of robotics that promotes the co-presence and cooperation of humans and robots in common workspaces. Physical vicinity and interaction between humans and robots, combined with the…

Robotics · Computer Science 2020-12-04 Mehrnoosh Askarpour

Pushing is a simple yet effective skill for robots to interact with and further change the environment. Related work has been mostly focused on utilizing it as a non-prehensile manipulation primitive for a robotic manipulator. However, it…

Robotics · Computer Science 2025-10-15 Zili Tang , Yuming Feng , Meng Guo

Humanoid robots are expected to operate in human-centered environments where safe and natural physical interaction is essential. However, most recent reinforcement learning (RL) policies emphasize rigid tracking and suppress external…

Robotics · Computer Science 2025-11-07 Qingzhou Lu , Yao Feng , Baiyu Shi , Michael Piseno , Zhenan Bao , C. Karen Liu

In this work, we introduce an adaptive control framework for human-robot collaborative transportation of objects with unknown deformation behaviour. The proposed framework takes as input the haptic information transmitted through the…

Robotics · Computer Science 2022-07-22 Doganay Sirintuna , Alberto Giammarino , Arash Ajoudani

Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing approaches are fundamentally constrained: retargeted data are often scarce or low-quality;…

Robotics · Computer Science 2026-03-04 Xialin He , Sirui Xu , Xinyao Li , Runpei Dong , Liuyu Bian , Yu-Xiong Wang , Liang-Yan Gui

Work-Related Musculoskeletal Disorders continue to be a major challenge in industrial environments, leading to reduced workforce participation, increased healthcare costs, and long-term disability. This study introduces a human-sensitive…

Robotics · Computer Science 2025-04-15 Vitor Martins , Sara M. Cerqueira , Mercedes Balcells , Elazer R Edelman , Cristina P. Santos

This paper introduces an upper limb postural optimization method for enhancing physical ergonomics and force manipulability during bimanual human-robot co-carrying tasks. Existing research typically emphasizes human safety or manipulative…

Robotics · Computer Science 2025-11-07 Chenzui Li , Yiming Chen , Xi Wu , Giacinto Barresi , Fei Chen

We present a planning and control approach for collaborative transportation of objects in space by a team of robots. Object and robots in microgravity environments are not subject to friction but are instead free floating. This property is…

Robotics · Computer Science 2025-04-29 Joris Verhagen , Jana Tumova

A robot needs multiple interaction modes to robustly collaborate with a human in complicated industrial tasks. We develop a Coexistence-and-Cooperation (CoCo) human-robot collaboration system. Coexistence mode enables the robot to work with…

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…

Robotics · Computer Science 2019-12-05 Jonas Tjomsland , Ali Shafti , A. Aldo Faisal

One of the key issues in human-robot collaboration is the development of computational models that allow robots to predict and adapt to human behavior. Much progress has been achieved in developing such models, as well as control techniques…

Humanoid robots deployed in real-world scenarios often need to carry unknown payloads, which introduce significant mismatch and degrade the effectiveness of simulation-to-reality reinforcement learning methods. To address this challenge, we…

Robotics · Computer Science 2026-03-17 Xingyi Wang , Chenyun Zhang , Weiji Xie , Chao Yu , Wei Song , Chenjia Bai , Shiqiang Zhu

We present a reinforcement learning framework for autonomous goalkeeping with humanoid robots in real-world scenarios. While prior work has demonstrated similar capabilities on quadrupedal platforms, humanoid goalkeeping introduces two…

Learning anticipation is a reasoning paradigm in multi-agent reinforcement learning, where agents, during learning, consider the anticipated learning of other agents. There has been substantial research into the role of learning…

Multiagent Systems · Computer Science 2023-04-04 Ariyan Bighashdel , Daan de Geus , Pavol Jancura , Gijs Dubbelman

Technological progress increasingly envisions the use of robots interacting with people in everyday life. Human-robot collaboration (HRC) is the approach that explores the interaction between a human and a robot, during the completion of a…

Robotics · Computer Science 2022-07-12 Francesco Semeraro , Alexander Griffiths , Angelo Cangelosi

In this study we evaluated human-robot collaboration models in an integrated human-robot operational system. An integrated work cell which includes a robotic arm working collaboratively with a human worker was specially designed for…

Robotics · Computer Science 2017-08-21 Lior Sayfeld , Ygal Peretz , Roy Someshwar , Yael Edan

One central goal of robotics is to enable robots to interact with the physical world. Traditional manipulation studies primarily focus on single robots and relatively small objects. However, factory and domestic environments often require…

Robotics · Computer Science 2026-05-26 Kun Song , Gaoming Chen , Shentao Ma , Ninglong Jin , Guangbao Zhao , Mingyu Ding , Zhenhua Xiong , Jia Pan

Collecting human demonstrations via teleoperation is a common approach for teaching robots task-specific skills. However, when only a limited number of demonstrations are available, policies are prone to entering out-of-distribution (OOD)…

Robotics · Computer Science 2026-04-07 Rui Yan , Zaitian Gongye , Lars Paulsen , Xuxin Cheng , Xiaolong Wang