MIT roboticists debate the future of robotics, data, and computing - The Robot Report

At the IEEE International Conference on Robotics and Automation (ICRA), leading roboticists debated the future direction of robotics, focusing on whether advances will be driven primarily by code-based models or data-driven approaches. The panel, moderated by Ken Goldberg of UC Berkeley and featuring experts such as Daniela Rus, Russ Tedrake, Leslie Kaelbling, and others, highlighted a growing divide in the field. Rus and Tedrake strongly advocated for data-centric methods, emphasizing that real-world robotics requires machines to learn from extensive, multimodal datasets capturing human actions and environmental variability. They argued that traditional physics-based models work well in controlled settings but fail to generalize to unpredictable, human-centered tasks. Rus’s team at MIT’s CSAIL is pioneering this approach by collecting detailed sensor data on everyday human activities like cooking, capturing nuances such as gaze and force interactions to train AI systems that enable robots to generalize and adapt. Tedrake illustrated how scaling data enables robots to develop "common sense" for dexter