Architecture for autonomy

In 2002 Defence R&D Canada changed research direction from pure tele-operated land vehicles to general autonomy for land, air, and sea craft. The unique constraints of the military environment coupled with the complexity of autonomous systems drove DRDC to carefully plan a research and development infrastructure that would provide state of the art tools without restricting research scope. DRDC's long term objectives for its autonomy program address disparate unmanned ground vehicle (UGV), unattended ground sensor (UGS), air (UAV), and subsea and surface (UUV and USV) vehicles operating together with minimal human oversight. Individually, these systems will range in complexity from simple reconnaissance mini-UAVs streaming video to sophisticated autonomous combat UGVs exploiting embedded and remote sensing. Together, these systems can provide low risk, long endurance, battlefield services assuming they can communicate and cooperate with manned and unmanned systems. A key enabling technology for this new research is a software architecture capable of meeting both DRDC's current and future requirements. DRDC built upon recent advances in the computing science field while developing its software architecture know as the Architecture for Autonomy (AFA). Although a well established practice in computing science, frameworks have only recently entered common use by unmanned vehicles. For industry and government, the complexity, cost, and time to re-implement stable systems often exceeds the perceived benefits of adopting a modern software infrastructure. Thus, most persevere with legacy software, adapting and modifying software when and wherever possible or necessary -- adopting strategic software frameworks only when no justifiable legacy exists. Conversely, academic programs with short one or two year projects frequently exploit strategic software frameworks but with little enduring impact. The open-source movement radically changes this picture. Academic frameworks, open to public scrutiny and modification, now rival commercial frameworks in both quality and economic impact. Further, industry now realizes that open source frameworks can reduce cost and risk of systems engineering. This paper describes the Architecture for Autonomy implemented by DRDC and how this architecture meets DRDC's current needs. It also presents an argument for why this architecture should also satisfy DRDC's future requirements as well.

[1]  Jack Collier,et al.  Software Systems for Robotics An Applied Research Perspective , 2006 .

[2]  Erann Gat,et al.  Experiences with an architecture for intelligent, reactive agents , 1997, J. Exp. Theor. Artif. Intell..

[3]  R. C. Coulter,et al.  Implementation of the Pure Pursuit Path Tracking Algorithm , 1992 .

[4]  Fintan Bolton,et al.  Pure CORBA: A Code-Intensive Premium Reference , 2001 .

[5]  Robert James Firby,et al.  Adaptive execution in complex dynamic worlds , 1989 .

[6]  Reid G. Simmons,et al.  Recent progress in local and global traversability for planetary rovers , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[7]  Gregory S. Broten,et al.  Frameworks and middleware for umanned ground vehicles , 2005, SPIE Defense + Commercial Sensing.

[8]  Hans Utz,et al.  Miro - middleware for mobile robot applications , 2002, IEEE Trans. Robotics Autom..

[9]  Daniel P. Schrage,et al.  An open platform for reconfigurable control , 2001 .

[10]  François Michaud,et al.  Code reusability tools for programming mobile robots , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[11]  Douglas C. Schmidt,et al.  An overview of the Real-Time CORBA specification , 2000, Computer.

[12]  G Broten,et al.  Engineering Review of ANCAUS/AVATAR: An Enabling Technology for the Autonomous Land Systems Program? , 2003 .

[13]  Robin R. Murphy,et al.  Artificial intelligence and mobile robots: case studies of successful robot systems , 1998 .

[14]  Jay Gowdy,et al.  Emergent Architectures: A Case Study for Outdoor Mobile Robots , 2000 .

[15]  James S. Albus,et al.  4-D/RCS: a reference model architecture for Demo III , 1997, Proceedings of the 1998 IEEE International Symposium on Intelligent Control (ISIC) held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) Intell.

[16]  Sebastian Thrun,et al.  Perspectives on standardization in mobile robot programming: the Carnegie Mellon Navigation (CARMEN) Toolkit , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[17]  Reid G. Simmons,et al.  Structured control for autonomous robots , 1994, IEEE Trans. Robotics Autom..

[18]  Maxim Likhachev,et al.  D*lite , 2002, AAAI/IAAI.

[19]  Larry Matthies,et al.  Stereo vision and rover navigation software for planetary exploration , 2002, Proceedings, IEEE Aerospace Conference.

[20]  Anders Orebäck,et al.  BERRA: a research architecture for service robots , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[21]  Jack Collier,et al.  Towards Distributed Intelligence , 2004 .

[22]  Richard T. Vaughan,et al.  The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems , 2003 .