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Spatial Reasoning with Guinness. University of Missouri, Columbia, MO. References. Acknowledgements. gesture. speech. PDA(NRL). GUI(EUT). robot. mapserver. SRserver. pose. palmserver. THE STARTING ARCHITECTURE. user commands and responses. oldest short term map. speech commands.
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Spatial Reasoning with Guinness University of Missouri, Columbia, MO References Acknowledgements
gesture speech PDA(NRL) GUI(EUT) robot mapserver SRserver pose palmserver THE STARTING ARCHITECTURE user commands and responses oldest short term map speech commands palmhelper sensor info robot pose robot pose continuous localization trulla corrections robot cmds encoders vfh sensor data long term map short term map
imageserver gesture speech PDA(MU) GUI(EUT) robot mapserver SRserver pose spatialview THE CURRENT ARCHITECTURE user commands and responses oldest short term map speech commands user commands and responses sketch log files Cortex sensor info robot pose robot_spatial robot pose continuous localization trulla corrections sensor data robot cmds robot cmds encoders vfh sensor data long term map short term map sketch log files
imageserver PDA(MU) gesture speech GUI(EUT) robot mapserver SRserver pose THE PLANNED ARCHITECTURE user commands and responses oldest short term map query & label speech commands SR & map info user commands and responses spatial behaviors Cortex sensor info robot pose robot pose robot commands continuous localization trulla obstacle avoidance corrections sketch directives & feedback sensor data robot cmds encoders vfh sensor data long term map short term map
SRserver Behind the table User: How many objects do you see? Robot: I am sensing four objects. User: Object 2 is a table. User: Describe the scene. Robot: There are objects on my front right. The object number 4 is mostly in front of me. The table is behind me. User: Go behind the table.
between object 1 and object 2 using the midpoint between closest points using the midpoint between centroids using the CFMD
Understanding Sketched Route Maps PATH DESCRIPTION GENERATED FROM THE SKETCHED ROUTE MAP 1. When table is mostly on the right and door is mostly to the rear (and close) Then Move forward 2. When chair is in front or mostly in front Then Turn right 3. When table is mostly on the right and chair is to the left rear Then Move forward 4. When cabinet is mostly in front Then Turn left 5. When ATM is in front or mostly in front Then Move forward 6. When cabinet is mostly to the rear and tree is mostly on the left and ATM is mostly in front Then Stop
References [1] M. Skubic, P. Matsakis, G. Chronis and J. Keller, "Generating Multi-Level Linguistic Spatial Descriptions from Range Sensor Readings Using the Histogram of Forces", Autonomous Robots, Vol. 14, No. 1, Jan., 2003, pp. 51-69. [2] M. Skubic, D. Perzanowski, S. Blisard, A. Schultz, W. Adams, M. Bugajska and D. Brock “Spatial Language for Human-Robot Dialogs,” IEEE Transactions on SMC, Part C, to appear in thespecial issue on Human-Robot Interaction. [3] M. Skubic, S. Blisard, C. Bailey, J.A. Adams and P. Matsakis, "Qualitative Analysis of Sketched Route Maps: Translating a Sketch into Linguistic Descriptions," IEEE Transactions on SMC Part B, to appear. [4] G. Chronis and M. Skubic, “Sketch-Based Navigation for Mobile Robots,” In Proc. of the IEEE 2003 Intl. Conf. on Fuzzy Systems, May, 2003, St. Louis, MO. [5] G. Scott, J.M. Keller, M. Skubic and R.H. Luke III, “Face Recognition for Homeland Security: A Computational Intelligence Approach,” In Proc. of the IEEE 2003 Intl. Conf. on Fuzzy Systems, May, 2003, St. Louis, MO.
Guinness and Gang From left to right George Chronis, Grant Scott, Dr. Marge Skubic, Matt Williams, Craig Bailey, Bob Luke, Charlie Huggard and Sam Blisard Missing: Dr. Jim Keller
Sketch-Based Navigation The robot traversing the sketched route The sketched route map
Sketch-Based Navigation The robot traversing the sketched route The digitized sketched route map
Sketch-Based Navigation The robot traversing the sketched route The digitized sketched route map
Acknowledgements This work has been supported by ONR and the U.S. Naval Research Lab. Natural language understanding is accomplished using a system developed by NRL, called Nautilus [Wauchope, 2000]. We also want to acknowledge the help of Dr. Pascal Matsakis.