A Robotic System for Reaching in Dense Clutter that Integrates Model Predictive Control, Learning, Haptic Mapping, and Planning
robotic system, model predictive control, haptic mapping
We present a system that enables a robot to reach locations in dense clutter using only haptic sensing. Our system integrates model predictive control , learned initial conditions , tactile recognition of object types , haptic mapping, and geometric planning to efficiently reach locations using whole- arm tactile sensing . 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.
RERC TechSAge Publications
Ira A. Fulton College of Engineering and Technology
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