Prehensile tails, capable of suspending the entire body weight of an animal, have evolved in parallel in New World monkeys (Platyrrhini): once in the Atelinae (Alouatta, Ateles, Brachyteles, Lagothrix), and once in the Cebinae (Cebus, Sapajus). Structurally, the prehensile tails of atelines and cebines share morphological features that distinguish them from nonprehensile tails, including longer...

This work presents a novel active visuo-tactile based framework for robotic systems to accurately estimate pose of objects in dense cluttered environments. The scene representation is derived using declutter graph (DG) which describes the relationship among decluttering by leveraging semantic segmentation and grasp affordances networks. formulation allows robots efficiently workspace autonomous...

Robotic manipulation in cluttered environments requires synergistic planning among prehensile and non-prehensile actions. Previous works on sampling-based Task Motion Planning (TAMP) algorithms, e.g. PDDLStream, provide a fast generalizable solution for multi-modal manipulation. However, they are likely to fail scenarios where no collision-free grasping approaches can be sampled without prelimi...

This letter describes an approach to achieve well-known Chinese cooking art stir-fry on a bimanual robot system. Stir-fry requires sequence of highly dynamic coordinated movements, which is usually difficult learn for chef, let alone transfer robots. In this letter, we define canonical movement, and then propose decoupled framework learning deformable object manipulation from human demonstratio...

This paper describes our experiments with a distributed manipulation system. We study a system in which multiple robots cooperate to move large objects such as furniture and boxes using a constrained prehensile manipulation mode, by wrapping ropes around them. The system consists of three manipulation skills: tieing ropes around objects, affecting translations using a flossing manipulation gait...

We explore learning-based approaches for feedback control of a dexterous five-finger hand performing non-prehensile manipulation. First we learn local controllers that are able to perform the task starting at a predefined initial state. These controllers are constructed using trajectory optimization with respect to locally-linear time-varying models learned directly from sensor data. In some ca...