Human-to-Robot Handovers is one of the four competition tracks within the 11th Robotic Grasping and Manipulation Competition (RGMC) that will be held during the IEEE/RAS International Conference on Robotics and Automation (ICRA) 2026 in Vienna, Austria.
This is a unique opportunity to benchmark your work with the state-of-the-art and advance this robotic task in real-world conditions. You can either bring your own robots to the competition site or request a robot provided by the RGMC sponsors (UR5e or Franka Emika Panda) based on availability (see Application form for more details) Moreover, Mathworks will provide free Matlab licenses to participants.
You will also be invited to present your work at an IROS Workshop (TBC) and contribute a research article to the Topical Collection on "Advancing Robotic Grasping and Manipulation for the Real-World" within Autonomous Robots (see here).
Please fill out the application form to participate in RGMC 2026. Deadline: February 9th, 2026 for full consideration. We will continue receiving applications after that date and may consider them based on the availability of the participant spots and the readiness of the solution. If you have any questions, please email Berk Calli at bcalli@wpi.edu.
The real-time estimation through vision perception of the physical properties of objects manipulated by humans is important to inform the control of robots and perform accurate and safe grasps of objects handed over by humans. However, estimating the physical properties of previously unseen objects using only inexpensive cameras is challenging due to illumination variations, transparencies, reflective surfaces, and occlusions caused both by the human and the robot. Our dynamic human-to-robot handovers track is based on an affordable experimental setup that does not use a motion capture system, markers, or prior knowledge of specific object models. The track focuses on food containers and drinking glasses that vary in shape and size, and may be empty or filled with an unknown amount of unknown content. The goal is to assess the generalisation capabilities of the robotic control when handing over previously unseen objects filled (or not) with unknown content, hence with a different and unknown mass and stiffness. No object properties are initially known to the robot (or the team) that must infer these properties on-the-fly, during the execution of the dynamic handover, through perception of the scene.
The track will involve a qualification phase in which teams can perform the handover configurations of the CORSMAL Benchmark protocol remotely in their laboratory. Please see also the starting kit and documentation for preparing your solution.
Track organisers
Changjae Oh, Queen Mary University of London (UK)
Andrea Cavallaro, École polytechnique fédérale de Lausanne (Switzerland)
Alessio Xompero, Queen Mary University of London (UK)
Contacts
If you have any questions or enquiries related to the competition track, please contact Dr. Changjae Oh or Prof. Andrea Cavallaro.
If you have any general questions or other enquiries related to the Robotic and Grasping Manipulation Competition,
please visit the RGMC webpage.
