Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions

The need for autonomous underwater vehicles (AUVs) for intervention missions becomes greater as they can perform underwater tasks requiring physical contacts with the underwater environment, such as underwater plug-in/plug-out, construction and repair, cable streaming, mine hunting, munitions retrieval, and scientific sampling. This paper describes a semi-autonomous underwater vehicle for intervention missions that has multiple on-board CPUs, redundant sensors and actuators, on-board power source and a robotic manipulator for dextrous underwater performance. Such a complex robotic vehicle system requires advanced control software architecture for on-board intelligence with a wide range of sensors and actuators to carry out required missions. In this paper, AUV control architectures are reviewed and a sensor data bus based control architecture (SDBCA) is presented. SDBCA is a modified hierarchical architecture that offers good controllability and stability while sensor data bus increases flexibility of system design, making it possible to have a prompt response from high-level control with respect to low-level sensor data. The overall sensor input mechanism of SDBCA becomes similar to the sensor input mechanism of subsumption architecture.

[1]  Joan Batlle,et al.  Recent trends in control architectures for autonomous underwater vehicles , 1999, Int. J. Syst. Sci..

[2]  Junku Yuh,et al.  An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[3]  Hayato Kondo,et al.  Object observation in detail by the AUV "Tri-Dog 1" with laser pointers , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[4]  Tamaki Ura,et al.  Development of an autonomous underwater robot “Twin-Burger” for testing intelligent behaviors in realistic environments , 1996, Auton. Robots.

[5]  R. Peter Bonasso,et al.  Using parallel program specifications for reactive control of underwater vehicles , 1992, Applied Intelligence.

[6]  Stefan B. Williams,et al.  Behavior-based control for autonomous underwater exploration , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[7]  Junku Yuh,et al.  Task description language for underwater robots , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[8]  G. Bruzzone,et al.  AMADEUS: dual-arm workcell for co-ordinated and dexterous manipulation , 1998, IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259).

[9]  R. Lakshmi,et al.  A coordinated control of an underwater vehicle and robotic manipulator , 1991, J. Field Robotics.

[10]  Junku Yuh,et al.  Application of non-regressor based adaptive control to an underwater mobile platform-mounted manipulator , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[11]  Junku Yuh,et al.  HIGH-LEVEL CONTROL OF AUTONOMOUS ROBOTS USING A BEHAVIOR-BASED SCHEME AND REINFORCEMENT LEARNING , 2002 .

[12]  Robert B. McGhee,et al.  Autonomous underwater vehicle control coordination using a tri-level hybrid software architecture , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[13]  S. McClaran,et al.  Architecture of the Texas A&M Autonomous Underwater Vehicle Controller , 1996, Proceedings of Symposium on Autonomous Underwater Vehicle Technology.

[14]  Rolf Pfeifer,et al.  Understanding intelligence , 2020, Inequality by Design.

[15]  J.J. Leonard,et al.  A behavior-based approach to adaptive feature detection and following with autonomous underwater vehicles , 2000, IEEE Journal of Oceanic Engineering.

[16]  Junku Yuh,et al.  On AUV control architecture , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[17]  F. Lobo Pereira,et al.  Multiple AUVS for coastal oceanography , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[18]  Maja Matijasevic,et al.  Control architectures for autonomous underwater vehicles , 1997 .

[19]  X. Zheng.  Layered control of a practical AUV , 1992, Proceedings of the 1992 Symposium on Autonomous Underwater Vehicle Technology.

[20]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[21]  Fernando Lobo Pereira,et al.  IES an open system for underwater inspection , 1999, Oceans '99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008).

[22]  T. Ura,et al.  Construction and operation of four autonomous underwater vehicles for lake survey , 2002, Proceedings of the 2002 Interntional Symposium on Underwater Technology (Cat. No.02EX556).

[23]  Kenichi Asakawa,et al.  Cable tracking for autonomous underwater vehicle , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).

[24]  E. Gat.  On Three-Layer Architectures , 1997 .

[25]  Rodney A. Brooks,et al.  Cambrian Intelligence: The Early History of the New AI , 1999 .