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Safe manipulation in unknown, crowded environments via sensor-based interleaving planner: interleaving software and sensitive skin hardware

Published online by Cambridge University Press:  11 February 2016

Dugan Um  and
Dongseok Ryu
Dugan Um*
Affiliation:
Texas A&M University - Corpus Christi 6300 Ocean Dr. Unit 5797 Corpus Christi, TX 78412, USA
Dongseok Ryu
Affiliation:
Korea Atomic Energy Research Institute 989-111 Daedeok-daero, Yuseong-gu Daejeon, 305-353, South Korea Email: sayryu@kaeri.re.kr
*
*Corresponding author. E-mail: dugan.um@tamucc.edu
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Summary

As various robots are anticipated to coexist with humans in the near future, safe manipulation in unknown, cluttered environments becomes an important issue. Manipulation in an unknown environment, however, has been proven to be NP-Hard and the risk of unexpected human--robot collision hampers the dawning of the era of human--robot coexistence. We propose a non-contact-based sensitive skin as a means to provide safe manipulation hardware and interleaving planning between the workspace and the configuration space as software to solve manipulation problems in unknown, crowded environments. Novelty of the paper resides in demonstration of real time and yet complete path planning in an uncertain and crowded environment. To that end, we introduce the framework of the sensor-based interleaving planner (SBIP) whereby search completeness and safe manipulation are both guaranteed in cluttered environments. We study an interleaving mechanism between sensation in a workspace and execution in the corresponding configuration space for real-time planning in uncertain environments, thus the name interleaving planner implies.

Applications of the proposed system include manipulators of a humanoid robot, surgical manipulators, and robotic manipulators working in hazardous and uncertain environments such as underwater, unexplored planets, and unstructured indoor spaces.

Keywords

Sensor-based planningpoint cloudunknown environment motion planningcollision avoidance

Information

Type
Articles
Information
Robotica , Volume 35 , Issue 5 , May 2017 , pp. 1176 - 1191
Copyright
Copyright © Cambridge University Press 2016 

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