Visual obstacle detection and avoidance for indoor mobile robots

This study is a part of a joint team eort to transform a small-scale model carinto an autonomous moving robot. This transformation includes several routinesthat are essential and attached together. Integration of various equipment on themodel car is the rst step of that routine which is shared among dierent thesisstudies conducted at RAVLAB (Robotics and Autonomous Vehicles Laboratory)of Isk University. Hence, the resulting hardware system which is explained inthis thesis is mostly the co-produce of RAVLAB team.The integration is followed by implementing the software required to establishcontrol and communication links between dierent units. During this thesis, theauthor has developed a multi-threaded main control software to facilitate obstacleavoiding movements of the robot while reading and analyzing sensory inputs.This thesis study mainly focuses on detection of the obstacles with visual informationcollected from an ordinary color camera. The main obstacle detectionalgorithm that is proposed in this thesis is adapted from a powerful backgroundsubtraction algorithm ViBe [1] (Visual Background Extractor). The proposedalgorithm uses the model of the ground plane in order to detect obstacles. Adierent ground plane model is kept for each pixel location as in ViBe. Theproposed algorithm is robust against illumination dierences, shadows and thechanges in the appearance of the ground plane. A comparison is provided (usingground truth data) with another obstacle detection algorithm [2] which also usesa ground plane based model to detect obstacles. The results of the proposedalgorithm under dierent conditions compared to a counterpart.In addition to the obstacle detection, during this study two obstacle avoidancealgorithms are developed to facilitate navigation of the robot in indoor environments.The experiments show that the robot is able to move while avoidingobstacles by using ultrasonic sensors as well as using the visual camera input.