Mission planning and simulation of unmanned aerial vehicles with a GIS-based framework

Mission Planning software uses Geographic Information Systems (GIS) sources and dynamic aggregation of geo-referenced data to provide an information-rich context for human-directed creation of missions that are, for the most part, vehicle-independent. This requires a connection between the universal Mission Planner and an heterogeneous groups of unmanned aerial vehicles (UAVs), payloads and associated software tools. The developed abstraction mechanism is the Aerial Vehicle Control Language (AVCL), in which the missions are expressed. The ultimate goal is the easy integration of vehicles developed by different research groups with existing systems. It has been tested with our real-time small helicopter simulator.

[1]  Christiaan J. J. Paredis,et al.  RAVE: a real and virtual environment for multiple mobile robot systems , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[2]  S. M. Smith,et al.  Mission command macros for autonomous underwater vehicle , 1999, Oceans '99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No.99CH37008).

[3]  C. Barrouil,et al.  An integrated navigation system for a long range AUV , 1998, IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259).

[4]  A. Barrientos,et al.  Modeling and identification of a small unmanned helicopter , 2004, Proceedings World Automation Congress, 2004..

[5]  Sivasankar Ramarasu.  Vision based navigation for an unmanned aerial vehicle , 2007 .

[6]  Antonio Barrientos,et al.  Identification of a small unmanned helicopter model using genetic algorithms , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Patrick Doherty.  Advanced Research with Autonomous Unmanned Aerial Vehicles , 2004, KR.

[8]  Josué Jr. Guimarães Ramos,et al.  Internet-based solutions in the development and operation of an unmanned robotic airship , 2003 .

[9]  Donna Peuquet,et al.  Making Space for Time: Issues in Space-Time Data Representation , 2001, GeoInformatica.

[10]  Bruno Sinopoli,et al.  Vision based navigation for an unmanned aerial vehicle , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[11]  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).

[12]  Christiane Duarte,et al.  Defining a common control language for multiple autonomous vehicle operation , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[13]  Fumin Zhang,et al.  The MDLe Engine -- A Software Tool for Hybrid Motion Control , 2000 .

[14]  Donna Peuquet,et al.  Making Space for Time: Issues in Space-Time Data Representation , 1999, Proceedings. Tenth International Workshop on Database and Expert Systems Applications. DEXA 99.

[15]  K.S. Tso,et al.  A multi-agent operator interface for unmanned aerial vehicles , 1999, Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033).

[16]  S. Shankar Sastry,et al.  Flying robots: modeling, control and decision making , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[17]  Krzysztof Kuchcinski,et al.  The WITAS Unmanned Aerial Vehicle Project , 2000, ECAI.