Basic knowledge about cognitive robotics

Question

I am interested to learn about cognitive robotics and its application in situation assessment using natural language processing esp monitoring of human activities/disaster management.The processing would involve data visualization techniques. Can anyone suggest what is the starting point,which books to follow,the programming language/platform and some links to reference/example codes to begin with.Do I need to use ROS(robotic Operating system)?I came across GOLOG and situational calculus.Can anyone suggest where to download GOLOG & how to use it?Any other help would be highly solicited.

Answer 1

NLP and visualization are not typically associated with robotics; at least in the research literature. Furthermore, disaster management and activity monitoring are more commonly associated with sensor networks, and pervasive computing; see, for example

• DistressNet: A Wireless Ad Hoc and Sensor Network Architecture for Situation Management in Disaster Response. This high-level (aka "systems") papers discusses the architectural details.
• Real-Time Activity Classification Using Ambient and Wearable Sensors
• A Knowledge-Driven Approach to Activity Recognition in Smart Homes
• Activity knowledge transfer in smart environments
• A hierarchical approach to real-time activity recognition in body sensor networks

Activity analysis is a very active topic so I can only give you a sampling of the literature. These are not explicitly about monitoring activity related to disasters but I'm not sure what your needs are. It seems like you are more interested in modeling activities from text, so I would also recommend you investigate sentiment analysis.

On the robotics side, IEEE has a relevant journal called IEEE Transactions on Affective Computing. The Robotics and Computational Intelligence societies have numerous publications, too.

These books seem to be up your alley. Note that the reigning paradigm for belief representation today is Bayesian probability. If you want to read about that try Probabilistic Robotics. For a comprehensive general guide see Springer's Handbook of Robotics.