NDLI: Constrained filtering with contact detection data for the localization and registration of continuum robots in flexible environments

Content Provider	IEEE Xplore Digital Library
Author	Tully, S. Bajo, A. Kantor, G. Choset, H. Simaan, N.
Copyright Year	2012
Description	Author affiliation: Mechanical Engineering Department at Vanderbilt University, Nashville, TN 37240, USA (Bajo, A.; Simaan, N.) \|\| Electrical and Computer Engineering Department at Carnegie Mellon University, Pittsburgh, PA 15213, USA (Tully, S.) \|\| Robotics Institute at Carnegie Mellon University, Pittsburgh, PA 15213, USA (Kantor, G.; Choset, H.)
Abstract	This paper presents a novel filtering technique that uses contact detection data and environmental stiffness estimates to register and localize a robot with respect to an a priori 3D surface model. The algorithm leverages geometric constraints within a Kalman filter framework and relies on two distinct update procedures: 1) an equality constrained step for when the robot is forcefully contacting the environment, and 2) an inequality constrained step for when the robot lies in the free-space of the environment. This filtering procedure registers the robot by incrementally eliminating probabilistically infeasible state space regions until a high likelihood solution emerges. In addition to registration and localization, the algorithm can estimate the deformation of the surface model and can detect false positives with respect to contact estimation. This method is experimentally evaluated with an experiment involving a continuum robot interacting with a bench-top flexible structure. The presented algorithm produces an experimental error in registration (with respect to the end-effector position) of 1.1 mm, which is less than 0.8 percent of the robot length.
Starting Page	3388
Ending Page	3394
File Size	590009
Page Count	7
File Format	PDF
ISBN	9781467314039
ISSN	10504729
e-ISBN	9781467314053
e-ISBN	9781467314046
DOI	10.1109/ICRA.2012.6225080
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kalman filters Robot kinematics Robot sensing systems Uncertainty Estimation Vectors
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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