Tight Coupling between Manipulation and Perception using SLAM

A tight coupling between perception and manipulation is required for dynamic robots to react in a timely and appropriate manner to changes in the world. In conventional robotics, perception transforms visual information into internal models which are used by planning algorithms to generate trajectories for motion. Under this paradigm, it is possible for a plan to become stale if the robot or environment changes configuration before the robot can replan. Perception and actuation are only loosely coupled through planning; there is no rapid feedback or interplay between them. For a statically stable robot in a slowly changing environment, this is an appropriate strategy for manipulating the world. A tightly coupled system, by contrast, connects perception directly to actuation, allowing for rapid feedback. This tight coupling is important for a dynamically unstable robot which engages in active manipulation. In such robots, planning does not fall between perception and manipulation; rather planning creates the connection between perception and manipulation. We show that Simultaneous Localization and Mapping (SLAM) can be used as a tool to perform the tight coupling for a humanoid robot with numerous proprioceptive and exteroceptive sensors. Three different approaches to generate a motion plan for grabbing a piece of debris is evaluated using for Atlas humanoid robot. Results indicate higher success rate and accuracy for motion plans that implement tight coupling between perception and manipulation using SLAM.