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A cooperative human-robot learning system for remote robotic operations using a virtual reality (VR) interface is presented. The paper describes the overall system architecture, and the VR telerobotic system interface. Initial tests using o­n-line control through the VR interface for the task of shaking out the contents of a plastic bag are presented. The system employs several state-action policies. System states are defined by: type of bag, status of robot, and environment. Actions are defined by initial grasping point, lift and shake trajectory. A policy is a set of state-action pairs to perform a robotic task. The system starts with knowledge of the individual operators of the robot arm, such as opening and closing the gripper, but it has no policy for deciding when these operators are not appropriate, nor does it have knowledge about the special properties of the bags. An optimal policy is defined as the best action for a given state that is learned from experience and human guidance. A policy is found to be beneficial if a bag was grabbed successfully and all its contents extracted.

This paper describes a telerobotic system operated through a virtual reality (VR) interface. A least squares method is used to find the transformation mapping, from the virtual to real environments. Results revealed an average transformation error of 3mm. The system was tested for the task of planning minimum time shaking trajectories to discharge the contents of a suspicious package o­nto a workstation platform. Performance times to carry out the task directly through the VR interface showed rapid learning, reaching standard time (288 seconds) within 7 to 8 trials - exhibiting a learning rate of 0.79.

The last stage of any type of automatic surveillance system is the interpretation of the acquired information from its sensors. This work focuses o­n the interpretation of motion pictures taken from a surveillance camera, i.e.; image understanding. A prototype of a fuzzy expert system is presented which can describe in a natural language like manner, simple human activity in the field of view of a surveillance camera. The system is comprised of three components: a pre-processing module for image segmentation and feature extraction, an object identification fuzzy expert system (static model), and an action identification fuzzy expert system (dynamic temporal model). The system was tested o­n a video segment of a pedestrian passageway taken by a surveillance camera.

The last stage of any type of automatic surveillance system is the interpretation of the acquired information from the sensors. This work focuses o­n the interpretation of motion pictures taken from a surveillance camera, i.e.; image understanding. An expert system is presented which can describe in a natural language like, simple human activity in the field of view of a surveillance camera. The system has three different components: a pre-processing module for image segmentation and feature extraction, an object identification expert system (static model), and an action identification expert system (dynamic temporal model). The system was tested o­n a video segment of a pedestrian passageway taken by a surveillance camera.

Just added a video demonstrating the well-known McGurk Effect to the downloads section of this site. Thanks to Josh Lawrence for submitting the video.

A workshop on Formal Semantics and Cross-Linguistic Data is being held from August 15-19, 2005 in Edinburgh, Scotland. as part of the European Summer School on Logic, Language and Information (ESSLLI 2005). More info is available here.

The 4th workshop on Knowledge and Reasoning in Practical Dialogue Systems willl take place on July 30, 2005 in Edinburgh, Scotland at the 19th International Joint Conference on Artificial Intelligence. More info is available here.

The Document Understanding Conference (DUC) 2005 will be held in Vancouver, BC from October 9-10, 2005. More information is available here.

The Second Conference o­n Email and Anti-Spam will be held at Stanford University (Palo Alto, CA), July 21-22, 2005. The Submission deadline is March 15, 2005.

Back in July of 2004 I had to modify the permission system on this site to require users to register in order to make comments because of problems with spam. This had the negative side effect of blocking unregistered users from both submitting news and, moreover, trying to register!

Everything should be fixed now, and I apologize for any inconvenience.

Once again, anyone can submit news to this site.