Object Transportation

Object transportation research focuses on developing robust and efficient methods for robots, individually or collaboratively, to move objects of varying shapes, sizes, and fragility. Current efforts concentrate on improving path planning and control algorithms, often employing reinforcement learning, factor graph optimization, and model predictive control to handle complex scenarios, including unknown object properties and unstructured environments. These advancements are crucial for automating tasks in logistics, search and rescue, and human-robot collaboration, improving efficiency and safety in diverse applications.