We started the SHAARE associate team, between Auctus (Inria) and the IRiS lab (Kaist) with a joint seminar. We presented to each others some of our research interests in shared haptics, to better identify the framework for our future collaboration. Talks Huseyin Tugcan Dinc, PhD at IRiS lab, Three passivity-based approaches for stable haptic control Alexis Boulay, PhD at Auctus and Farm3, From Virtual Fixture to Active Constraint: a configurable haptic guide. [Read More]
The Auctus team was happy to host the visit of Thomas Flayols and Virgile Batto, collaborators from the Gepetto team at LAAS (CNRS). They presented their recent works on the design and control of quadruped and bipedal robots. Virgile’s PhD Thesis is part of a close collaboration between the two teams about the design of a dynamic robot leg. Talks Thomas Flayols, CNRS Research Engineer at LAAS, Ongoing research and mechatronic development on legged robots at LAAS: The ODRI open motor controllers and quadruped designs. [Read More]
The SHAARE associate team is created in 2024 between the IRiS lab at KAIST and the Auctus team at Inria, to share our complementary methodological orientations in haptic shared control. Together, we aim at developing shared-control approaches that, either, better guide the human through adaptive haptic guidance, or adjust the robot behavior according to the human gestures. The IRiS lab develops virtual-fixture feedback, generated from a task description given by the user. [Read More]
The Auctus team is delighted to receive the visit of Philip Long on November 6 and 7. Dr. Philip Long is a Lecturer in Robotics & Automation at Atlantic Technological University, Galway (ATU), Ireland and currently PI of the SFI Robomate project. His research interests include human-robot collaboration, sensor-based control of robot manipulators, cable-driven parallel robots and flexible manufacturing. He has extensive experience in technology transfer projects in robotics, having worked in both industry and academia for over 15 years. [Read More]
Abstract This thesis is based on vision of the future where robotics and industry are centred around humans, emphasising collaboration between humans and robots rather than mere automation. In this collaborative future, robots serve as active assistants, coexisting closely with humans and engaging in physical interactions to execute tasks. Such symbiotic systems leverage the unique abilities of both humans and robots, enhancing efficiency and prioritising human safety and well-being through personalised robotic assistance. [Read More]
The Auctus team is delighted to receive the visit of Ludovic Righetti on October 23 and 24. Ludovic Righetti is an associate professor at the Tandon School of Engineering of New York University. Currently on sabbatical leave, he is a visiting researcher at the LAAS-CNRS in Toulouse. He holds an Engineering Diploma in Computer Science and a Doctorate in Science from the Ecole Polytechnique Fédérale de Lausanne. He was previously a postdoctoral fellow at the University of Southern California and a group leader at the Max-Planck Institute for Intelligent Systems. [Read More]
Abstract Collaborative robotics involves the transformation of industrial robots to function in shared workspaces alongside humans, resulting in more compact and manageable robotic systems. This evolution necessitates a reevaluation of the requirements for robot controllers. Safety remains paramount, but robots must also adapt to dynamic contexts where objects are in constant motion, and conditions are ever-changing as people carry out their tasks. To address these challenges, this work proposes using Model Predictive Control (MPC) to empower the robot to dynamically adjust its operations in a responsive manner. [Read More]
Demonstration at Robocup23

Demonstration at Robocup23

The Auctus team manned a demonstration stand at the robocup. We took advantage of this opportunity to test our MPC based algorithms in a playful experience. Players were given small balls to throw into the large Plexiglas basket at the foot of the robot. The robot must prevent the marble from falling into the basket. To do this, he’s equipped with a tiny landing net. Behind this seemingly simple game runs an algorithm to detect the ball’s landing point, as well as our real-time MPC algorithm to move the robot, taking full account of the robot’s capabilities. [Read More]