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IEEE Robotics & Automation Magazine

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Natural Multimodal Fusion-Based Human–Robot Interaction: Application With Voice and Deictic Posture via Large Language Model

June 29, 2026 by Yuzhi Lai, Shenghai Yuan, Youssef Nassar, Mingyu Fan, Atmaraaj Gopal, Arihiro Yorita, Naoyuki Kubota, Matthias Rätsch

Abstract: Translating human intent into robot commands is crucial for the future of service robots in an aging society. Existing human–robot interaction (HRI) systems relying on gestures or verbal commands are impractical for the elderly, due to difficulties with complex syntax or sign language. To address the challenge, this article introduces a multimodal interaction … [Read more...] about Natural Multimodal Fusion-Based Human–Robot Interaction: Application With Voice and Deictic Posture via Large Language Model

Vision-Based Policy Learning for High-Speed Autonomous Racing: A Two-Phase Learning Paradigm

April 17, 2026 by Haoran Xu Xianwei Chen Yilin Lang Qinyuan Ren College of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China

Abstract: Robotic navigation in complex environments remains a critical research challenge. Traditional navigation methods focus on optimal trajectory generation within fixed free workspace, therefore struggling in environments lacking viable paths to the goal, such as disaster zones or cluttered warehouses. To address this problem, we propose AINav, an adaptive … [Read more...] about Vision-Based Policy Learning for High-Speed Autonomous Racing: A Two-Phase Learning Paradigm

Vision-Based Policy Learning for High-Speed Autonomous Racing: A Two-Phase Learning Paradigm

April 17, 2026 by Haoran Xu Xianwei Chen Yilin Lang Qinyuan Ren

Abstract: Motion planning for autonomous vision-based car racing is a challenging task in robotics. Classical racing systems divide the task into numerous submodules, undermining computational efficiency and leading to error propagation. Previous studies have demonstrated impressive reinforcement learning (RL) results for end-to-end autonomous driving. However, RL exhibits … [Read more...] about Vision-Based Policy Learning for High-Speed Autonomous Racing: A Two-Phase Learning Paradigm

The Developments and Challenges Toward Dexterous and Embodied Robotic Manipulation: A Survey

April 17, 2026 by Gaofeng Li Ruize Wang Peisen Xu Qi Ye Jiming Chen

Abstract: OKAchieving humanlike dexterous robotic manipulation remains a central goal and a pivotal challenge in robotics. The development of artificial intelligence (AI) has allowed rapid progress in robotic manipulation. This article summarizes the evolution of robotic manipulation from mechanical programming to embodied intelligence, alongside the transition from simple … [Read more...] about The Developments and Challenges Toward Dexterous and Embodied Robotic Manipulation: A Survey

Sex Robots and the AI Act

December 15, 2025 by Carlotta Rigotti Eduard Fosch-Villaronga

Abstract: The emergence of sex robots—human-like machines offering sexual and emotional services—has ignited contentious debates over their societal impact. Advocates glorify their potential to provide companionship, meet sexual needs, and diversify intimate experiences, while critics warn of risks, including the perpetuation of harmful stereotypes, hindered human … [Read more...] about Sex Robots and the AI Act

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About the Magazine

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.