LOBOT - A Review

Small sized ground robotic vehicles have great potential to be deployed in situations that are either uncomfortable for humans or simply too tedious. For example, a robot may become part of industrial operations, or become part of a senior citizen’s life, or become a tour guide for an exhibition center. The robot is kept as small as possible to allow access through narrow passageways such as a tunnel. To fulfill these missions, the robotic vehicle often has to obtain its accurate localization in real time. Considering the difficulty or impossibility in frequent calibration or the management of external facilities, it is desirable to have a self - contained positioning system for the robot: ideally, the localization system should be completely integrated onto t he robot instead of requiring external facilities to obtain the position; the system should work indoors and outdoors without any human involvement such as manual calibration or management. Meanwhile, the cost is expected to be as low as possible. There exist various localization schemes for ground robotic vehicles. These techniques normally utilize GPS, inertial sensors, radio signals, or visual processing. GPS often becomes inoperable in certain environments such as indoors or in wild forests. A dditionally, the GPS operations consume power quickly. As an alternative, a localization system may use various waves including electromagnetic waves of various frequencies. The radio - based positioning is among the most popular techniques. This technolog y requires a set of external devices to generate or receive radio signal; as the reference nodes, these external devices should have known positions. The accuracy of the radio - based positioning strongly depends on the proper calibration of the reference de vices and the target node, as well as a friendly radio environment. Maintaining such a positioning system can be costly and difficult in terms of additional hardware intensive tuning, and environmental management. It is also vulnerable to interference from other signals, thus affecting the accuracy of positioning. Another category of solutions is vision techniques for mobile robot navigation. Generally, these techniques heavily rely on sophisticated techniques on the recognition of an object or shape from i mages and often have restricted spatial and visional requirements. The performance usually strongly depends on the environment in which the robot operates and the localization suffers frequent failure. Additionally, they may require a known map of the envi ronment. Overall, the vision - based positioning is relatively costly and difficult to implement or maintain