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