Control Synthesis for Dynamic Contact Manipulation

Siddhartha Srinivasa
doctoral dissertation, tech. report CMU-RI-TR-05-33, Robotics Institute, Carnegie Mellon University, September, 2005


Download
  • Adobe portable document format (pdf) (10MB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
Manipulation is the art of moving things. At the heart of the problem, an object needs to be moved from start to goal by a robot that is in contact with the object. The contacts serve two purposes: they transmit forces and impose motion constraints on the object. Even if a robot can precisely control its own motion, it is constrained by the interactions at the contacts for control of the motion of the object. Contact interactions are governed by the laws of Coulomb friction and are nonlinear and non-Newtonian.

Current solutions to the manipulation problem decompose the problem into first solving for the forces required to produce a desired object motion and then commanding the robot to apply the requisite force. This imposed decomposition assumes that the robot is capable of producing the commanded forces and velocities required for manipulation. However, this assumption is broken in dynamic manipulation, where the robot operates close to actuator saturation.

In this thesis, we explore the planning and control of dynamic manipulation subject to actuator constraints. We describe a mapping of the Coulomb friction constraints and actuator constraints into a common space, obtaining a unified contact acceleration constraint. We propose two techniques for using this constraint to generate analytical trajectories for the dynamic manipulation problem. In the first technique of time-scaling, we decouple the problem into computing a feasible path followed by selecting the speed of motion along the path that satisfies the constraint. In the second technique of task and shape decomposition, we recognize that the constraint resides in a low dimensional subspace of the system state space and project the system dynamics onto, and orthogonal to that subspace. We use a feedback controller in the constraint space and plan for the orthogonal unconstrained freedoms. Finally, we demonstrate our techniques on two dynamic manipulation tasks and a constrained, nonholonomic system.


Notes
Associated Center(s) / Consortia: Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Manipulation Lab
Number of pages: 141

Text Reference
Siddhartha Srinivasa, "Control Synthesis for Dynamic Contact Manipulation," doctoral dissertation, tech. report CMU-RI-TR-05-33, Robotics Institute, Carnegie Mellon University, September, 2005

BibTeX Reference
@phdthesis{Srinivasa_2005_5146,
   author = "Siddhartha Srinivasa",
   title = "Control Synthesis for Dynamic Contact Manipulation",
   booktitle = "",
   school = "Robotics Institute, Carnegie Mellon University",
   month = "September",
   year = "2005",
   number= "CMU-RI-TR-05-33",
   address= "Pittsburgh, PA",
}