Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

After decades of using robots in mostly "robot-friendly” industrial environments which are typically structured, uncluttered and well understood, robots today have been successfully fielded in "human-friendly " environments such as museums, office buildings, department stores, and homes. These environments are typically uncertain, unstructured and mostly cluttered.

Grasping and manipulation is a central skill for a robot. It can impact its environment using its gripper. The field of robot grasping and manipulation is reaching an important milestone. In recent years, many robots have demonstrated that they can reliably perform basic grasps on unknown objects in unstructured environments. However, these robots are still far away from being capable of human-level manipulation skills such as in-hand manipulation of objects, interactions with non-rigid objects, and multi-object tasks such as stacking and tool-usage. As such, advanced manipulations that involve interacting with uncertain real-world environments pose major problems for current approaches and traditional methods that depend on accurate models of the robot and its surroundings.

The objective of this research proposal is to develop an integrated system that can plan, grasp, and learn how to grasp objects in uncertain environments. This work can have a significant impact on many applications ranging from manufacturing to precision agriculture.