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

dc.contributor.author Bhattacharjee, Tapomayukh
dc.contributor.author Grice, Phillip M.
dc.contributor.author Kapusta, Ariel
dc.contributor.author Killpack, Marc D.
dc.contributor.author Park, Daehyung
dc.contributor.author Kemp, Charles C.
dc.contributor.corporatename Georgia Institute of Technology. Institute for Robotics and Intelligent Machines en_US
dc.contributor.corporatename Georgia Institute of Technology. Healthcare Robotics Lab en_US
dc.contributor.corporatename Brigham Young University. Department of Mechanical Engineering en_US
dc.date.accessioned 2015-05-06T17:04:00Z
dc.date.available 2015-05-06T17:04:00Z
dc.date.issued 2014-09
dc.description ©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. en_US
dc.description Presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014) - 3rd Workshop on Robots in Clutter: Perception and Interaction in Clutter, 14-18 September, 2014, Chicago, IL.
dc.description.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. en_US
dc.embargo.terms null en_US
dc.identifier.citation Bhattacharjee, Tapomayukh; Grice, Phillip M.; Kapusta, Ariel; Killpack, Marc D.; Park, Daehyung; & Kemp, Charles C. (2014). “A Robotic System for Reaching in Dense Clutter that Integrates Model Predictive Control, Learning, Haptic Mapping, and Planning”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014) - 3rd Workshop on Robots in Clutter: Perception and Interaction in Clutter, 14-18 September. en_US
dc.identifier.uri http://hdl.handle.net/1853/53336
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers
dc.subject Dense clutter en_US
dc.subject Haptic sensing en_US
dc.subject Whole-arm tactile sensing en_US
dc.title A Robotic System for Reaching in Dense Clutter that Integrates Model Predictive Control, Learning, Haptic Mapping, and Planning en_US
dc.type Text
dc.type.genre Post-print
dc.type.genre Proceedings
dspace.entity.type Publication
local.contributor.author Kemp, Charles C.
local.contributor.corporatename Healthcare Robotics Lab
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
local.contributor.corporatename Rehabilitation Engineering Research Center on Technologies to Support Aging-in-Place for People with Long-Term Disabilities
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