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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

Collaborative robots are being increasingly utilized in industrial production lines due to their efficiency and accuracy. However, the close proximity between humans and robots can pose safety risks due to the robot's high-speed movements…

Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control…

Humans show specialized strategies for efficient collaboration. Transferring similar strategies to humanoid robots can improve their capability to interact with other agents, leading the way to complex collaborative scenarios with multiple…

This paper presents a method for designing energy-aware collaboration tasks between humans and robots, and generating corresponding trajectories to carry out those tasks. The method involves using high-level specifications expressed as…

Robotics · Computer Science 2023-06-06 Giuseppe Silano , Amr Afifi , Martin Saska , Antonio Franchi

A prototype of modular networked robot for autonomous monitoring works with full control over web through wireless connection has been developed. The robot is equipped with a particular set of built-in analyzing tools and appropriate…

Robotics · Computer Science 2008-09-05 I. Firmansyah , Z. Akbar , B. Hermanto , L. T. Handoko

Applying micro-patterns to surfaces has been shown to impart useful physical properties such as drag reduction and hydrophobicity. However, current manufacturing techniques cannot produce micro-patterned surfaces at scale due to high-cost…

Robotics · Computer Science 2026-03-20 Annalisa T. Taylor , Malachi Landis , Ping Guo , Todd D. Murphey

Humans can teleoperate robots to accomplish complex manipulation tasks. Imitation learning has emerged as a powerful framework that leverages human teleoperated demonstrations to teach robots new skills. However, the performance of the…

Robotics · Computer Science 2024-07-19 Philipp Wu , Yide Shentu , Zhongke Yi , Xingyu Lin , Pieter Abbeel

Robots applied in therapeutic scenarios, for instance in the therapy of individuals with Autism Spectrum Disorder, are sometimes used for imitation learning activities in which a person needs to repeat motions by the robot. To simplify the…

Robotics · Computer Science 2022-07-26 Natalia Quiroga , Alex Mitrevski , Paul G. Plöger

Bio-hybrid systems---close couplings of natural organisms with technology---are high potential and still underexplored. In existing work, robots have mostly influenced group behaviors of animals. We explore the possibilities of mixing…

Neural and Evolutionary Computing · Computer Science 2018-04-20 Mostafa Wahby , Mary Katherine Heinrich , Daniel Nicolas Hofstadler , Payam Zahadat , Sebastian Risi , Phil Ayres , Thomas Schmickl , Heiko Hamann

This work aims to tackle the intent recognition problem in Human-Robot Collaborative assembly scenarios. Precisely, we consider an interactive assembly of a wooden stool where the robot fetches the pieces in the correct order and the human…

Nowadays, industries are showing a growing interest in human-robot collaboration, particularly for shared tasks. This requires intelligent strategies to plan a robot's motions, considering both task constraints and human-specific factors…

Ergonomics is a key factor to consider when designing control architectures for effective physical collaborations between humans and humanoid robots. In contrast, ergonomic indexes are often overlooked in the robot design phase, which leads…

Similar to humans, robots benefit from interacting with their environment through a number of different sensor modalities, such as vision, touch, sound. However, learning from different sensor modalities is difficult, because the learning…

Robotics · Computer Science 2019-10-10 Martina Zambelli , Antoine Cully , Yiannis Demiris

Bimanual manipulation needs robots to be sensitive on the grasp force which is hard to be accurately detected. This paper proposes RL framework for enhancing the grasp quality during the bimanual manipulation. This framework is based on…

Robotics · Computer Science 2024-01-17 Jingyi Li

This study proposes a novel imitation learning approach for the stochastic generation of human-like rhythmic wave gestures and their modulation for effective non-verbal communication through a probabilistic formulation using joint angle…

Robotics · Computer Science 2020-03-09 Mihalis Panteris , Simon Manschitz , Sylvain Calinon

The ability to use random objects as tools in a generalizable manner is a missing piece in robots' intelligence today to boost their versatility and problem-solving capabilities. State-of-the-art robotic tool usage methods focused on…

Robotics · Computer Science 2025-10-30 Bohan Wu , Paul de La Sayette , Li Fei-Fei , Roberto Martín-Martín

To coordinate actions with an interaction partner requires a constant exchange of sensorimotor signals. Humans acquire these skills in infancy and early childhood mostly by imitation learning and active engagement with a skilled partner.…

Machine Learning · Computer Science 2019-10-15 Judith Bütepage , Ali Ghadirzadeh , Özge Öztimur Karadag , Mårten Björkman , Danica Kragic

Employing a teleoperation system for gathering demonstrations offers the potential for more efficient learning of robot manipulation. However, teleoperating a robot arm equipped with a dexterous hand or gripper, via a teleoperation system…

The assembly of printed circuit boards (PCBs) is one of the standard processes in chip production, directly contributing to the quality and performance of the chips. In the automated PCB assembly process, machine vision and coordinate…

Robotics · Computer Science 2026-01-13 Jieyang Peng , Dongkun Wang , Junkai Zhao , Yunfei Teng , Andreas Kimmig , Xiaoming Tao , Jivka Ovtcharova