Towards Semantically Intelligent Robots

Abstract

Approaches are needed for providing advanced autonomous wheeled robots with a sense of self, immediate ambience, and mission. The following list of abilities would form the desired feature set of such approaches: self-localization, detection and correction of course deviation errors, faster and more reliable identification of friend or foe, simultaneous localization and mapping in uncharted environments without necessarily depending on external assistance, and being able to serve as web services. Situations, where enhanced robots with such rich feature sets come to play, span competitions such as line following, cooperative mini sumo fighting, and cooperative labyrinth discovery. In this chapter we look into how such features may be realized towards creating intelligent robots. Currently through-cell localization in robots mainly relies on availability of shaft-encoders. In this regard, we would like to firstly present a simple-to-implement through-cell localization approach for robots even without a shaft-encoder in order to empower them to traverse approximately on the desired course (curve or linear) and end up registered properly at the desired target position. Researchers have presented ways including fuzzyand neural-based control systems for correcting the navigation deviation error. By providing a formulation for deviation error, especially during turning curves, and then applying reverse formulation to correct it, our self-corrective gyroscope-accelerometerencoder cascade control system adjusts the robot even more. When the robot detects that it has yawed off course, the system affects the requisite maneuvering and its timing in order to correct the deviation from course. Next step is to facilitate robots with ability of Friend-or-Foe (FoF) identification for cooperative multi-robot tasks. Mini-sumo team robots are well-known case-in-point where FoF identification capability would be most welcome whereas absolute positioning of teammates is not practical. Our simple-to-implement FoF identification does not require two-way communication as it only relies on decryption of payload in one direction. It is shown that the replay attack is not feasible due to high computation complexity as the communication is encrypted and timestamp is inserted in the messages. Our hardware implementation of cooperative robots incorporates a gyroscope chipset and rotary radar which is able to sense the direction and distance to detected object. Studying dynamics of robots allows finding solutions to attack even stronger enemy from sides so they will not be able to resist. Besides, there are certain situations that robots must evade or even try escaping instead of facing a fight. Our experimental work here attempts to illustrate situations of real battlefields of cooperative mini-sumo competitions as an example of localization, mapping, and collaborative problem solving in uncharted environments.