In recent years, robotic technology has improved significantly, aided by cutting-edge scientific research studies and innovative industrial designs. It has taken a progressive leap from the coordinated world of industry to the less-ordered domestic domain with great advancements in sensor technology and computational intelligence. It is beginning to prove more useful than a robot vacuum cleaner or a mere plaything in human-centric spaces. This has created an imminent need for robust intelligence for a robot to move optimally with high efficiency and collision-free navigation. This research provides valuable insights into all significant stages required for autonomous navigation in dynamic cluttered environments and makes several important contributions in the area.A unique and real-time method for global path planning and collision avoidance for navigation of a mobile robot in complex time varying environments is developed. An occupancy-based three dimensional (3D) grid map and model-based obstacle prediction are employed to represent the dynamic environment. Path planning and obstacle avoidance are performed by applying a cost-evaluation function on time-space Distance Transforms to uniquely produce the optimal path at the time of planning. Dealing with uncertainty with regard to the position of obstacles for a given navigation task is accommodated by introducing the notion of probabilities to the algorithm. The spatio-temporal cost evaluation based path planning algorithm provides the key contribution of this research.A robust method of pose estimation and tracking for a mobile robot is also investigated. The technique utilises an overhead panoramic vision camera in an indoor cluttered environment with the robot workspace of a two-dimensional planar surface. It is fast and does not require any unwarping of the panoramic view. A unique system, combining mean-shift, Kalman Filter and Hough Transform-based tracking, is used to improve the result. Experiments are conducted confirming that the system is capable of reliably localising and tracking the robot in cluttered scenes with variations of illumination and periods of occlusion.The thesis commences by describing the design of a real-time open-source 3D simulation platform based on a game engine. The platform is primarily aimed towards research in mobile robotics, in-game character manipulation, visual surveillance-related research and high quality synthetic video generation. It provided the initial test-bed for this research to analyse ideas and algorithms including path planning, prior to the physical realisation experiments.Finally, a complete navigation system is integrated for a wheel-based mobile robot verifying the innovations in a real-world scenario. The system will be incorporated into a larger project that is aimed towards the enhancement of robotic assistive technologies for elderly and disabled people.