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IEEE Robotics & Automation Magazine

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Features

A Robotic System for Transanal Endoscopic Microsurgery: Design, Dexterity Optimization, and Prototyping

June 24, 2025 by Jichen Li, Shuxin Wang, Zhiqiang Zhang, Chaoyang Shi

This paper proposes a master-slave operated robotic system that features the novel slave manipulator with a modular distal continuum section to address the shortcomings of traditional transanal endoscopic microsurgery (TEM). The slave manipulator consists of two 7-DoF surgical instruments and a 5-DoF endoscopic arm that are designed with distal continuum structures and unfolded … [Read more...] about A Robotic System for Transanal Endoscopic Microsurgery: Design, Dexterity Optimization, and Prototyping

Transurethral Surgical Robot: Achieving Efficient En Bloc Resection of Bladder Tumor

June 24, 2025 by Muneaki Miyasaka, Jiajun Liu, Wenjie Lai, Yu Xi Terence Law, Gerald Lim, Banjamin Quek, Ziting Wang, Qing Hui Wu, Edmund Chiong, Soo Jay Phee

Bladder cancer ranks as the 10th most common cancer globally. Currently, the standard surgical approach for bladder tumor removal involves transurethral piecemeal resection, which carries high recurrence (60%) and perforation (12%) rates. Although various techniques and robotic systems have been developed for en-bloc tumor resection, achieving a negative resection margin … [Read more...] about Transurethral Surgical Robot: Achieving Efficient En Bloc Resection of Bladder Tumor

Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-Free Design

June 24, 2025 by Vassil Atanassov, Jiatao Ding, Jens Kober, Ioannis Havoutis, Cosimo Della Santina

Deep reinforcement learning (DRL) has emerged as a promising solution to mastering explosive and versatile quadrupedal jumping skills. However, current DRL-based frameworks usually rely on pre-existing reference trajectories obtained by capturing animal motions or transferring experience from existing controllers. This work aims to prove that learning dynamic jumping is … [Read more...] about Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-Free Design

Reinforcement Learning for High-Speed Quadrupedal Locomotion With Motor Operating Region Constraints: Mitigating Motor Model Discrepancies through Torque Clipping in Realistic Motor Operating Region

June 24, 2025 by Young-Ha Shin, Tae-Gyu Song, Gwanghyeon Ji, Hae-Won Park

This article presents a method for achieving high-speed running of a quadruped robot by considering the actuator torque–speed operating region in reinforcement learning. The physical properties and constraints of the actuator are included in the training process to reduce state transitions that are infeasible in the real world due to motor torque–speed limitations. The gait … [Read more...] about Reinforcement Learning for High-Speed Quadrupedal Locomotion With Motor Operating Region Constraints: Mitigating Motor Model Discrepancies through Torque Clipping in Realistic Motor Operating Region

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

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IEEE Robotics & Automation Magazine (RAM) has over 14,000 readers who are the people who drive this remarkable technology. More than half work in basic research and many of the others are top level engineers and decision-makers in industry.  This magazine highlights new concepts in Robotics and Automation that are applied to real-world systems. It delivers tutorial and survey papers by distinguished experts in the field, organizes focused special issues on hot topics, and provides a forum for disseminating and discussing emerging trends, novel achievements, and selected news relevant to the development of the whole community active in these fields worldwide.

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