A Robotic System for Reaching in Dense Clutter that Integrates Model Predictive Control, Learning, Haptic Mapping, and Planning

Authors

Tapomayukh Bhattacharjee
Phillip Grice
Ariel Kapusta
Marc D. Killpack, Brigham Young University - ProvoFollow
Daehyung Park
Charles Kemp

Keywords

robotic system, model predictive control, haptic mapping

Abstract

We present a system that enables a robot to reach locations in dense clutter using only haptic sensing. Our system integrates model predictive control [1], learned initial conditions [2], tactile recognition of object types [3], haptic mapping, and geometric planning to efficiently reach locations using whole- arm tactile sensing [4]. We motivate our work, present a system architecture, summarize each component of the system, and present results from our evaluation of the system reaching to target locations in dense artificial foliage.

BYU ScholarsArchive Citation

Bhattacharjee, Tapomayukh; Grice, Phillip; Kapusta, Ariel; Killpack, Marc D.; Park, Daehyung; and Kemp, Charles, "A Robotic System for Reaching in Dense Clutter that Integrates Model Predictive Control, Learning, Haptic Mapping, and Planning" (2014). Faculty Publications. 3213.
https://scholarsarchive.byu.edu/facpub/3213

Document Type

Peer-Reviewed Article

Publication Date

2014

Permanent URL

http://hdl.lib.byu.edu/1877/6025

Publisher

RERC TechSAge Publications

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Mechanical Engineering

University Standing at Time of Publication

Assistant Professor

Copyright Status

© Georgia Institute of Technology