It is essential in many applications that mobile robots localize themselves with respect to an unknown environment. This means that the robot must build a map of its environment and then localize using the map. This process is called simultaneous localization and mapping (SLAM). This paper presents an iterative solution to the landmark initialization problem inherent in a bearing-only implementation of SLAM. No prior knowledge of the environment is required, and furthermore, there are no requirements about having the data association problem solved. Once landmarks are initialized, they are inserted into an extended Kalman Filter (EKF) to solve the SLAM problem. Both indoor and outdoor experiments are presented to validate the method.

In this work we introduce a new concept of a search and rescue robotic system that is composed of an elephant trunk-like robot mounted on a mobile base. This system is capable not only of inspecting areas reachable by the mobile base but also to inspect unreachable areas such as small cracks, and pipes, using the camera mounted on its elephant trunk robot. In the report we describe the mechanical structure of the elephant trunk robot, the kinematic analysis of the structure, the robot control, and its human interface systems.