Paper
18 June 2015 An ontology to enable optimized task partitioning in human-robot collaboration for warehouse kitting operations
Ashis Gopal Banerjee, Andrew Barnes, Krishnanand N. Kaipa, Jiashun Liu, Shaurya Shriyam, Nadir Shah, Satyandra K. Gupta
Author Affiliations +
Abstract
Collaborative teams of human operators and mobile ground robots are becoming popular in manufacturing plants to assist humans with a lot of the repetitive tasks such as the packing of related objects into different units, an operation known as kitting. In this paper, we present an ontology to provide a unified representation of all kitting-related tasks, which are decomposed into atomic actions that are either computational involving sensing, perception, planning, and control, or physical involving actuation and manipulation. The ontology is then used in a stochastic integer linear program for optimum partitioning of the atomic tasks between the robots and humans. Preliminary experiments on a single robot, single human case yield promising results where the kitting operations are completed with lower durations and manipulation failure rates using human-robot partnership versus just the human or only the robot. This success is achieved by the robot seeking human assistance for visual perception tasks while performing the other tasks primarily on its own.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ashis Gopal Banerjee, Andrew Barnes, Krishnanand N. Kaipa, Jiashun Liu, Shaurya Shriyam, Nadir Shah, and Satyandra K. Gupta "An ontology to enable optimized task partitioning in human-robot collaboration for warehouse kitting operations", Proc. SPIE 9494, Next-Generation Robotics II; and Machine Intelligence and Bio-inspired Computation: Theory and Applications IX, 94940H (18 June 2015); https://doi.org/10.1117/12.2181346
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CITATIONS
Cited by 12 scholarly publications and 1 patent.
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KEYWORDS
Robots

Stochastic processes

Manufacturing

Visualization

Clouds

3D modeling

Cameras

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