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Can robots pick and sort apples reliably in unstructured orchard environments using integrated mobile manipulation systems? The group is the PI and lead developer for an Automated and Integrated Mobile System (AIMS) project to develop an efficient robotic apple harvester funded through a USDA Specialty Crop Research Initiative. The researchers design cloud-enabled vehicle control and sensing methods to address connectivity, control and privacy in connected and automated vehicles as described in the CAREER project. The team builds soft multi-arm robotic manipulators (SMART) and applies learning-based controllers to enable safer, compliant human-robot collaboration. The group applies learning and control of robot systems combined with vehicle dynamics and optimal control to improve autonomous mobility and robotic manipulation.
Research focus
What this lab works on
Robotics and Autonomous VehiclesIntelligent Transportation SystemsReinforcement LearningVehicle DynamicsOptimal Control
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