Mobile robots applications are growing everyday. Some of their applications include exploring unknown planets like Mars, finding woundeds in an earthquake and helping them and etc. The most important characteristic of mobile robots is their ability to navigate through the environment autonomously in order to reach the goal point. The type of operational environment of a mobile robot can be divided to two broad inter-ideograph; TEXT-ALIGN: justify; MARGIN: 0cm 0cm 5pt; unicode-bidi: embed; DIRECTION: ltr" The goal of this thesis is the modification of TangentBug algorithm so that it can be used on Ackerman mobile robots. The robot environment is assumed to be unknown and offroad. By offroad, we mean that no prior assumptions on the environment characteristic (like having roads or any guiding signs) are made. The proposed navigation method of this thesis is based on TangentBug algorithm (one of the most famous Bug algorithms). Despite its robustness, TangentBug has some shortcomings for example it assumes that the robot is a point (with zero width and length); also it ignores the maneuver limitations of the robot. In this thesis, the original TangentBug algorithm is modified so that it can be used as the navigation algorithm on a real car-like robot. To this end, potential field obstacle avoidance method is integrated with TangentBug and the kinematic equations of the car-like robot are taken into account by utilizing a method similar to VFH+ obstacle avoidance algorithm. To evaluate the proposed method, it is compared with the original TangentBug in simulated environment. In addition to the simulation, the proposed approach is implemented and tested on a real robot. Keywords: Autonomous navigation, Unknown environment, Obstacle avoidance, Sensor-based
