Unstructured environmental mapping using low cost sensors

Achieving an innovative and intelligent low cost sensor system for an autonomous mobile robot to navigate and map the unstructured environment is the main aim of this paper. The environment or the map is unstructured in the sense that, the obstacles in the environment are unknown. There are various approaches to this problem, but the focused approach here can give robust performance of low cost sensor based localisation and mapping. The robust performance is quantified by explicit bounds of the position estimate of a mobile robot and to make it to build the environmental map of its surroundings. The mobile robots generally carry dead reckoning sensors such as wheel encoders and inertial sensors (INS), accelerometers and gyroscopes, to measure the acceleration and the angular rate, while the obstacle detection and map-making is done with the low cost sensor such as time-of-flight ultrasonic sensors. The localisation task is achieved by combining the different source of sensor measurements which are complementary and therefore compensate for each other's limitations, so that the resulting performance of the sensor system is better than of its individual components which provides high richness in the mapping task.