• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • IEEE.org
  • IEEE Xplore
  • IEEE Standards
  • IEEE Spectrum
  • More Sites

IEEE Robotics & Automation Magazine

  • IEEE.org
  • IEEE Xplore
  • IEEE Standards
  • IEEE Spectrum
  • More Sites

Legged locomotion

A Biomimetic and Energy-Efficient Leg Design for a Humanoid Robot: An Exclusively Linear-Actuated Implementation

June 29, 2026 by Junyang Wang, XueAi Li, Fenglei Ni, Baoshi Cao, Le Qi, Hong Liu, Xiangji Wang, Teng Zhang

Abstract: The mobility and manipulation of bipedal humanoid robots always depend on their legs, which account for balance and may substantially accelerate energy consumption, especially when the lower body is expected to be stationary. To this end, this article presents a biomimetic and energy-efficient design for bipedal robots’ legs and extensively demonstrates its … [Read more...] about A Biomimetic and Energy-Efficient Leg Design for a Humanoid Robot: An Exclusively Linear-Actuated Implementation

Cross-Embodiment Imitation: Learning a Unified Latent Space for Multirobot Control

April 17, 2026 by Yashuai Yan Dongheui Lee

Abstract: We present a scalable framework for cross-embodiment humanoid robot control by learning a shared latent representation that unifies motion across humans and diverse humanoid platforms, including single-arm, dual-arm, and legged humanoid robots. Our method proceeds in two stages. First, we construct a decoupled latent space that captures localized motion patterns … [Read more...] about Cross-Embodiment Imitation: Learning a Unified Latent Space for Multirobot Control

DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition

April 17, 2026 by Yuki Kadokawa Jonas Frey Takahiro Miki Takamitsu Matsubara Marco Hutter ETH Zurich, Zurich, Switzerland

Abstract: Preference-based reinforcement learning (PBRL) enables policy learning through simple queries comparing trajectories from a single policy. While human responses to these queries make it possible to learn policies aligned with human preferences, PBRL suffers from low query efficiency, as policy bias limits trajectory diversity and reduces the number of … [Read more...] about DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition

Learning Perceptive Legged Robot Locomotion in the Real World: A Systematic Review

April 17, 2026 by Irfan Tito Kurniawan Wei Zhu Dai Owaki Mitsuhiro Hayashibe

Abstract: Perception is essential for legged locomotion as it enables robots to anticipate upcoming terrains and obstacles, facilitating adaptive traversal of challenging environments. Recent advancements in learning methodologies and legged locomotion have fostered research on the integration of perception into legged robot locomotion controllers, allowing them to operate … [Read more...] about Learning Perceptive Legged Robot Locomotion in the Real World: A Systematic Review

Door-to-Door Parcel Delivery From Supply Point to User’s Home With Heterogeneous Robot Team: The euROBIN First-Year Robotics Hackathon

September 10, 2025 by Alejandro Suarez, Rainer Kartmann, Daniel Leidner, Luca Rossini, Johann Huber, Carlos Azevedo, Quentin Rouxel, Marko Bjelonic, Antonio Gonzalez-Morgado, Christian Dreher, Peter Schmaus, Arturo Laurenzi, François Hélénon, Rodrigo Serra, Jean-Baptiste Mouret, Lorenz Wellhausen, Vicente Perez-Sanchez, Jianfeng Gao, Adrian Simon Bauer, Alessio De Luca, Mouad Abrini, Rui Bettencourt, Olivier Rochel, Joonho Lee, Pablo Viana, Christoph Pohl, Nesrine Batti, Diego Vedelago, Vamsi Krishna Guda, Alexander Reske, Carlos Alvarez, Fabian Reister, Werner Friedl, Corrado Burchielli, Aline Baudry, Fabian Peller-Konrad, Thomas Gumpert, Luca Muratore, Philippe Gauthier, Franziska Krebs, Sebastian Jung, Lorenzo Baccelliere, Hippolyte Watrelot, Andre Meixner, Anne Köpken, Mohamed Chetouani, Pascal Weiner, Florian Lay, Felix Hundhausen, Anne Reichert, Noémie Jaquier, Florian Schmidt, Marco Sewtz, Freek Stulp, Lioba Suchenwirth, Rudolph Triebel, Xuwei Wu, Begoña Arrue, Rebecca Schedl-Warpup, Marco Hutter, Serena Ivaldi, Pedro U. Lima, Stéphane Doncieux, Nikos Tsagarakis, Tamim Asfour, Anibal Ollero, Alin Albu-Schäffer

Logistics and service operations involving parcel preparation, delivery, and unpacking from a supply point to a user’s home could be carried out completely by robots in the near future, taking advantage of the capabilities of the different robot morphologies for the logistics, outdoor, and domestic environments. The use of robots for parcel delivery can contribute to the goals … [Read more...] about Door-to-Door Parcel Delivery From Supply Point to User’s Home With Heterogeneous Robot Team: The euROBIN First-Year Robotics Hackathon

Next Page »

Primary Sidebar

Current Issue

Get the entire issue now.

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.

Past Issues

Search

Footer

LINKS

Home | Contact IEEE | Accessibility |
Nondiscrimination  Policy | IEEE Ethics Reporting | Terms & Disclosures| IEEE Privacy Policy

© Copyright 2025 IEEE – All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

ABOUT US

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