SLAM-Based Spatial Memory for Behavior-Based Robots

Abstract Knowledge is essential for an autonomous robot to act intelligently when tasked with a mission. With recent leaps of progress, the paradigm of SLAM (Simultaneous Localization and Mapping) has emerged as an ideal source of spatial knowledge for autonomous robots. However, despite advancements in both paradigms of SLAM and robot control, research in the integration of these areas has been lacking and remained open to investigation. This paper presents an integration of SLAM into a behavior-based robotic system as a dynamically acquired spatial memory, which can be used to enable new behaviors and augment existing ones. The effectiveness of the integrated system is demonstrated with a biohazard search mission, where a robot is tasked to search and locate a biohazard within an unknown environment under a time constraint.

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

[2]  Sebastian Thrun,et al.  FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics , 2007 .

[3]  D A Henderson,et al.  The looming threat of bioterrorism. , 1999, Science.

[4]  Alexei Makarenko,et al.  An experiment in integrated exploration , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Ronald C. Arkin,et al.  Integrating behavioral, perceptual, and world knowledge in reactive navigation , 1990, Robotics Auton. Syst..

[6]  Hugh Durrant-Whyte,et al.  Simultaneous localization and mapping (SLAM): part II , 2006 .

[7]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[8]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[9]  Damian M. Lyons,et al.  A Software Tool for the Design of Critical Robot Missions with Performance Guarantees , 2013, CSER.

[10]  Damian M. Lyons,et al.  Designing autonomous robot missions with performance guarantees , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Ian D. Reid,et al.  On the comparison of uncertainty criteria for active SLAM , 2012, 2012 IEEE International Conference on Robotics and Automation.

[12]  Ronald C. Arkin,et al.  Usability evaluation of high-level user assistance for robot mission specification , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[13]  Shalabh Gupta,et al.  SLAM based adaptive navigation of AUVs for oil spill cleaning , 2014, 2014 Oceans - St. John's.

[14]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[15]  Damian M. Lyons,et al.  Verifying and validating multirobot missions , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Sven Behnke,et al.  Evaluating the Efficiency of Frontier-based Exploration Strategies , 2010, ISR/ROBOTIK.

[17]  Cyrill Stachniss,et al.  Hierarchical optimization on manifolds for online 2D and 3D mapping , 2010, 2010 IEEE International Conference on Robotics and Automation.

[18]  Wolfram Burgard,et al.  Exploration with active loop-closing for FastSLAM , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[19]  Gamini Dissanayake,et al.  Active SLAM in structured environments , 2008, 2008 IEEE International Conference on Robotics and Automation.

[20]  Lansing E Dickinson.  Military Role in Countering Terrorist Use of Weapons of Mass Destruction , 2012 .

[21]  Alexei Makarenko,et al.  Information based adaptive robotic exploration , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Tucker R. Balch,et al.  Avoiding the past: a simple but effective strategy for reactive navigation , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[23]  Sebastian Thrun,et al.  Simultaneous Localization and Mapping , 2008, Robotics and Cognitive Approaches to Spatial Mapping.

[24]  Frank Dellaert,et al.  iSAM: Incremental Smoothing and Mapping , 2008, IEEE Transactions on Robotics.

[25]  Ryan M. Eustice,et al.  Perception-driven navigation: Active visual SLAM for robotic area coverage , 2013, 2013 IEEE International Conference on Robotics and Automation.

[26]  R. K. Betts,et al.  The New Threat of Mass Destruction , 1998 .

[27]  Brian Yamauchi,et al.  A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[28]  Gamini Dissanayake,et al.  Active SLAM using Model Predictive Control and Attractor based Exploration , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[29]  Gordon Wyeth,et al.  Hybrid robot control and SLAM for persistent navigation and mapping , 2010, Robotics Auton. Syst..

[30]  Wolfram Burgard,et al.  A hybrid collision avoidance method for mobile robots , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[31]  Maja J. Mataric,et al.  Integration of representation into goal-driven behavior-based robots , 1992, IEEE Trans. Robotics Autom..

[32]  Ronald C. Arkin,et al.  Multiagent Mission Specification and Execution , 1997, Auton. Robots.

[33]  Nicholas Roy,et al.  Global A-Optimal Robot Exploration in SLAM , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.