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Robot kinematics

Large-Language-Model-Aided Assistive Robot for Single-Operator Bimanual Teleoperation: Introduction and Validation of a Flexible Assistance System

April 17, 2026 by Haolin Fei Songlin Ma School of Engineering, Lancaster University, Lancaster, U.K. Guanglong Du Elmira Yadollahi Hak-Keung Lam Angela Faragasso

Abstract: Bimanual teleoperation tasks are highly demanding for human operators, requiring the simultaneous control of two robotic arms while managing complex coordination and cognitive load. Current approaches to this challenge often rely on rigid control schemes or task-specific automations that do not adapt well to dynamic environments or varied operator needs. This … [Read more...] about Large-Language-Model-Aided Assistive Robot for Single-Operator Bimanual Teleoperation: Introduction and Validation of a Flexible Assistance System

PAPRLE: Plug-And-Play Robotic Limb Environment: A Modular Ecosystem for Robotic Limbs

April 17, 2026 by Obin Kwon Sankalp Yamsani Noboru Myers Sean Taylor Jooyoung Hong Kyungseo Park

Abstract: We introduce PAPRLE (plug-and-play robotic limb environment), a modular ecosystem that enables flexible placement and control of robotic limbs. With PAPRLE a user can change the arrangement of the robotic limbs and control them using a variety of input devices, including puppeteers, gaming controllers, and virtual reality (VR) devices. This versatility supports a … [Read more...] about PAPRLE: Plug-And-Play Robotic Limb Environment: A Modular Ecosystem for Robotic Limbs

Leveraging Embodied Mechanical Intelligence for Learning Decluttering Tasks: Gripper Design Boosts Learning

April 17, 2026 by Enrico Turco Valerio Bo Chiara Castellani Gionata Salvietti Monica Malvezzi Domenico Prattichizzo

Abstract: In this work, we investigate how a state-of-the-art grasp planner based on deep reinforcement learning performs when applied to a soft–rigid gripper in a decluttering task. The gripper, called Soft ScoopGripper (SSG), is endowed with a rigid scoop-shaped part that facilitates the interaction with the environment and with objects. We hypothesize that the clever … [Read more...] about Leveraging Embodied Mechanical Intelligence for Learning Decluttering Tasks: Gripper Design Boosts Learning

A Whole-Body Integrated AVATAR System: Implementation of Telepresence With Intuitive Control and Immersive Feedback

June 24, 2025 by Sungman Park, Junsoo Kim, Hojae Lee, Minwoong Jo, Dohoon Gong, Dawon Ju, Dami Won, Sihyeon Kim, Jinhyeok Oh, Hun Jang, Joonbum Bae,

This paper proposes an intuitive and immersive whole-body teleoperation system with motion-based control and multi-modal feedback. The system consists of an anthropomorphic teleoperated robot and a haptic interface platform. The teleoperated robot has dual arms with dexterous hands, a head with a neck, a waist, giving it a human-like appearance and a large range of motion … [Read more...] about A Whole-Body Integrated AVATAR System: Implementation of Telepresence With Intuitive Control and Immersive Feedback

Toward Fully Autonomous Aviation: PIBOT, a Humanoid Robot Pilot for Human-Centric Aircraft Cockpits

March 18, 2025 by Sungjae Min, Gyuree Kang, Hyungjoo Kim, David Hyunchul Shim

Humanoid robots have been considered ideal for automating daily tasks, though most research has centered on bipedal locomotion. Many activities we do routinely, such as driving a car, require real-time system manipulation as well as substantial field-specific knowledge. Recent breakthroughs in natural language processing, particularly with large language models (LLMs), are … [Read more...] about Toward Fully Autonomous Aviation: PIBOT, a Humanoid Robot Pilot for Human-Centric Aircraft Cockpits

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As the flagship magazine of the IEEE Robotics and Automation Society, IEEE Robotics and Automation Magazine (RAM) covers the latest developments in robotics and automation. Its scope ranges from cutting-edge technological advances to emerging social, economic, ethical, and policy issues shaping the field.  Published quarterly (March, June, September, and December), RAM features both high-impact original research articles written in an engaging and accessible style, as well as reviews, columns and opinion pieces addressing a wide range of timely topics.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.