Unlocking Agile and Object-Aware Loco-Manipulation
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Unlocking Agile and Object-Aware Loco-Manipulation
Fri, 24/01/2025 - 14:00 to 14:30
Location:
Speaker:
Dr Carlos Mastalli
Synopsis:
Recent advancements in model predictive control have enabled legged robots to perform agile maneuvers, such as backflips, with remarkable precision. However, these approaches often falter during manipulation tasks, where changes in dynamics caused by object interactions are not accounted for—highlighting the need for object-aware control strategies. In this talk, I will present our whole-body predictive controller and perceptive locomotion framework, which lay the groundwork for dynamic and adaptive robot behaviors. I will then introduce our recent efforts in optimal estimation of inertial parameters for objects interacting with our robots, enabling real-time identification during complex maneuvers. This capability is powered by advancements in parametric differential dynamic programming, analytical derivatives of parameterized dynamics, and smooth manifold representations of inertial properties.
Biography:
Dr. Carlos Mastalli is an Assistant Professor at Heriot-Watt University, UK, and a Research Scientist at the Florida Institute for Human & Machine Cognition (IHMC), USA. Carlos focuses on advancing both top-down approaches, which generate motor behaviors using principles from physics, group theory, inference, and optimization principles, and bottom-up approaches, which learn motor skills from sensory stimuli and experience. His interests span fundamental and experimental science for motor intelligence in robotics, along with accelerating robotics adoption in the industry. He leads the Robot Motor Intelligence (RoMI) Lab as part of the Edinburgh Center for Robotics and the UK’s National Robotarium. Besides his dedication to robotics, Carlos is committed to fostering a unique research environment. He champions the next generation of scientists and engineers, encourages interdisciplinary collaboration, and attracts and nurtures top-tier talent worldwide.