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Fetch Mobile Robot: Human-Robot Co-Transportation:
Developed an optimal control framework for human-robot co-transportation, ensuring safety and stability.
Modeled human behavioral and perception uncertainty toward multiple options for efficient collaboration.
Optimized robotic arm (7-DOF) joint angle selection using a deep learning method to enhance task efficiency and avoid potential singularities.
Developed a unified framework for mutual adaptation between humans and robots under uncertainties.
Implemented algorithms in robot hardware (Fetch Mobile Manipulator).
We presented our research project, "Human-Robot Co-Transportation with Human Uncertainty-Aware MPC and Pose Optimization," at ICRA 2024, Yokohama, Japan, in a workshop on Human-Robot Co-Manipulation. Our poster was selected as the Best Poster Finalist.
I had the opportunity to present our latest research project titled "Mitigating Human Uncertainties in Human-Robot Collaborative Transportation with Whole-Body Dynamics" at the IROS 2023 conference in Michigan, USA. Our work was featured as a 'Late Breaking Results' presentation, and we had the privilege of showcasing it through both a poster session and an oral presentation.