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A Mixed Initiative Approach to Human-Robot Interaction for Through-the-Door Operation

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-08-C-0315
Agency Tracking Number: 06SB2-0188
Amount: $749,956.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: SB062-009
Solicitation Number: 2006.2
Timeline
Solicitation Year: 2006
Award Year: 2008
Award Start Date (Proposal Award Date): 2008-04-25
Award End Date (Contract End Date): 2010-04-30
Small Business Information
15400 Calhoun Drive Suite 400
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Priya Ranjan
 Research Scientist
 (301) 294-5268
 pranjan@i-a-i.com
Business Contact
 Mark James
Title: Director, Contracts and P
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract

We propose an innovative, distributed multi-agent based mixed-initiative planning approach to facilitate true partnership among humans and robots useful in many tactical application environments including “through-the-door” and NIST’s search and rescue scenario. We leverage our distributed control framework (DCF) along with indoor positioning system like Cricket and OpenCV based vision for situational awareness, to coordinate shoulder-to-shoulder team building and provide intelligent support for agile execution. Algorithms wise, IAI will leverage hierarchical task network (HTN) representation to organize the team members and their task allocations efficiently in completely distributed and scalable manner. Additionally, we propose to build cognition models for humans and intent detection for overall optimal team performance. All capabilities required to demonstrate these tactical scenarios beginning with decomposition of tasks among the human and robots while coordinating partners’ actions in decision making will be developed and integrated seamlessly. Our approach is inherently robust and scalable as it leads to significant improvement in human situational awareness and human-robot camaraderie for better coordination and control of different activities required to complete missions in chaotic and disorganized scenarios. We will demonstrate the end to end scenario on distributed control platform (DCF) with multiple sensor and cognition modules readily available at IAI.

* Information listed above is at the time of submission. *

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