No abstract

Mobile robot navigation has become as a challenging problem over the last few decades. Despite the significant advances in this field, mobile robot researchers have yet to reach a comfortable level of satisfaction and yet still finding an improved algorithm for robot's navigation. In this paper, we proposed investigate the cognitive mapping algorithm that is been implemented to the mobile robot. This mobile robot will be given some inputs which are horizontal and vertical value and start and goal point and a task which is to move from start point to goal point. Some obstacles are also located in the arena and the mobile robot must be able to avoid any given obstacles to reach the goal point. The performance of the cognitive mapping algorithm is compared with an edge follower navigation algorithm, which is an algorithm for a mobile robot to navigate by following the edges or the wall. Based on the experiments that have been performed the cognitive mapping algorithm can be an alternative way for the robot's navigation systems.

Searching Mechanism is an important technique that is usually used by Search and Rescue team to find people especially victims for natural disasters. In this paper, we propose an exploration algorithm using quadcopter in simulation to discover an unknown area that is based on the expanding circle pattern for searching activities. Expanding circle searching pattern is a circular search procedure that is conducted by a series of distances around a fixed reference point, which can be used for unknown area exploration. The simulation is implemented in a swarm-based environment as it can increase the performance of robots for exploration compared to the non-swarm based environment. Based on the initial simulation result, the swarm-based exploration algorithm with the expanding circle pattern can maximize the searching area covered if compared with only having individual searching robot.