PRECISE SPEED ESTIMATION OF PHYSICALLY CONNECTED OFF-ROAD ROBOTIZED VEHICLES

Abstract

Numerous types of robots can now be created thanks to modern technology, including industrial, humanoid, or soft robots, robotic vehicles, etc. A popular research field in robotics now covers groups of robots that are self-organized, autonomous, cooperative, and coordinated amongst themselves, known as swarm robots. There are numerous examples of swarm robots in industry and in scientific research. In most of these examples, each robotic unit is not physically linked to other robotic units. There are far fewer examples of a group of robots where there is a physical connection such as a rope or a towing link between two robots. Connecting a few autonomous robotic vehicles by wire or cable, where a wire is held to be tightened, can form a kind of a movable fence. One of the main challenges in keeping the wire tight is synchronizing the motion of the robots. In order to achieve that, precise measurement of the speed of every robotized vehicle is needed. Measuring the RPM of the wheels is insufficient when robotized vehicles are traveling on a non-flat, slick terrain where wheel slide of one or more wheels is anticipated. The information from various sensors is combined in this study to demonstrate the use of artificial intelligence methods for accurate speed prediction of physically connected off-road autonomous robotized vehicles.