Force and Vision Resolvability for Assimilating Disparate Sensory Feedback

Bradley Nelson and Pradeep Khosla
tech. report CMU-RI-TR-95-11, Robotics Institute, Carnegie Mellon University, March, 1995


Download
  • Adobe portable document format (pdf) (461KB)
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
Force and vision sensors provide complementary information, yet they are fundamentally different sensing modalities. This implies that traditional sensor integration techniques that require common data representations are not appropriate for combining the feedback from these two disparate sensor. In this paper, we introduce the concept of vision and force sensor resolvability as a means of comparing the ability of the two sensing modes to provide useful information during robotic manipulation tasks. By monitoring the resolvability of the two sensing modes with respect to the task, the information provided by the disparate sensors can be seamlessly assimilated during task execution. A nonlinear force/vision servoing algorithm that uses force and vision resolvability to switch between sensing modes is proposed. The advantages of the assimilation technique is demonstrated during contact transitions between a stiff manipulator and rigid environment, a system configuration that easily becomes unstable when force control alone is used. Experimental results show that robust contact transitions are made by the proposed nonlinear controller while simultaneously satisfying the conflicting task requirements of fast approach velocities, maintaining stability, minimizing impact forces, and suppressing bounce between contact surfaces.

Notes
Sponsor: US Army Research Office, Sandia National Research Laboratories
Grant ID: DAAL03-91-G-0272, AC-3752D
Number of pages: 40

Text Reference
Bradley Nelson and Pradeep Khosla, "Force and Vision Resolvability for Assimilating Disparate Sensory Feedback," tech. report CMU-RI-TR-95-11, Robotics Institute, Carnegie Mellon University, March, 1995

BibTeX Reference
@techreport{Nelson_1995_370,
   author = "Bradley Nelson and Pradeep Khosla",
   title = "Force and Vision Resolvability for Assimilating Disparate Sensory Feedback",
   booktitle = "",
   institution = "Robotics Institute",
   month = "March",
   year = "1995",
   number= "CMU-RI-TR-95-11",
   address= "Pittsburgh, PA",
}