ICRA 2025 @Atlanta, USA

Awards at ICRA 2025

IDRA recieved few awards and research recognition at the 41st edition of ICRA, held in Atlanta (USA) in the days 18-23 May 2025.

IEEE RA-L Outstanding Associate Editor Award

We are pleased to congratulate Professor Daniele Fontanelli, who received the Outstanding Associate Editor Award for his contributions to the journal IEEE Robotics and Automation Letters (RA-L). This award recognizes his exceptional work in supporting the scientific community through rigorous, timely, and constructive editorial activity. His dedication to maintaining the quality and impact of one of the leading journals in robotics is an inspiration for our entire research group.

IEEE RA-L Best Paper Honorable Mention for Work on Safe Energy-Aware Robot Control

The paper A Novel Safety-Aware Energy Tank Formulation Based on Control Barrier Functions co-authored by Professor Matteo Saveriano, received the Best Paper Award – Honorable Mention from the editorial board of the IEEE Robotics and Automation Letters (RA-L) journal. The paper introduces a new approach to energy tank-based control that enhances robot safety and passivity during physical interaction with the environment. Traditional energy tanks ensure that robots do not generate unbounded energy, but they often rely on discrete switching logic that may cause abrupt behavior and fail to regulate power output — a critical safety concern. To address these limitations, the authors propose a continuous formulation of energy tanks using Control Barrier Functions (CBFs). This novel method allows for the simultaneous enforcement of energy and power constraints in a smooth and unified way. The result is a system that can adaptively scale robot commands to remain within safe operating limits, improving both the stability and safety of robots performing complex tasks like force control and variable stiffness regulation. The proposed method was validated in experiments involving real robotic hardware, demonstrating its effectiveness in limiting kinetic energy, ensuring passivity, and preventing unsafe behaviors even under dynamic and unpredictable interactions. This recognition highlights the growing impact of safety-aware, learning-enabled control strategies in the next generation of human-centered robotics.

Workshop Best Paper Award in Intelligent Manufacturing

The paper “MeshDMP: Motion Planning on Discrete Manifolds using Dynamic Movement Primitives”, presented by Matteo Dalle Vedove, received the Best Paper Award at the workshop The Future of Intelligent Manufacturing: From innovation to implementation. In this work, we introduce an innovative approach in the field of learning from demonstration, enabling robots to perform movements across complex surfaces. Just as a human can draw shapes on both flat and curved surfaces, our goal is to allow robots to learn and reproduce motions that adapt naturally to different geometries. We extended existing mathematical models of Dynamic Movement Primitives (DMPs) to support the learning, execution, and transfer of trajectories directly on 3D meshes — digital surface representations that are widely used in computer graphics and robotics. This allows, for example, teaching a robot a gesture on one surface and having it automatically adapt the motion to a completely different shape. To demonstrate the industrial potential of this method, our work includes an automatic system for generating cleaning trajectories over complex geometries — such as a car body — starting from a simple gesture like drawing a circle. The award, valued at $350, was sponsored by the IEEE Robotics and Automation Society (RAS) technical committees on Machine Learning for Automation and Digital Manufacturing and Human-Centered Automation, with the workshop organized under the patronage of Franka Robotics. The event featured presentations from international academic researchers and industry leaders, all focused on how cutting-edge robotics research can be transferred into real-world manufacturing to meet growing demands for flexibility and customization. We’re honored by this recognition and excited to continue developing technologies that bring advanced robot learning closer to industrial applications.

Workshop Best Paper Finalist in Planning and Control in Real World Scenarios

Finally, Elias Fontanari’s work, ‘Parallel-Constraint Model Predictive Control: Exploiting Parallel Computation for Improving Safety’ was selected as one of the three candidates for the workshop Beyond the Lab: Robust Planning and Control in Real World Scenarios best abstract award. Even if the prize was not won, the nomination recognised the quality of the work.