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The primary objective of a safe navigation algorithm is to guide the objectfrom its current position to the target position while avoiding any collisionwith the en-route obstacles, and the appropriate obstacle avoidance strategiesare the key factors to ensure safe navigation tasks in dynamic environments. Inthis report, three different obstacle avoidance strategies for safe navigationin dynamic environments have been presented. The biologically-inspirednavigation algorithm (BINA) is efficient in terms of avoidance time. Theequidistant based navigation algorithm (ENA) is able to achieve navigation taskwith in uncertain dynamic environments. The navigation algorithm algorithmbased on an integrated environment representation (NAIER) allows the object toseek a safe path through obstacles in unknown dynamic environment in ahuman-like fashion. The performances and features of the proposed navigationalgorithms are confirmed by extensive simulation results and experiments with areal non-holonomic mobile robot. The algorithms have been implemented on tworeal control systems: intelligent wheelchair and robotic hospital bed. Theperformance of the proposed algorithms with SAM and Flexbed demonstrate theircapabilities to achieve navigation tasks in complicated real time scenarios.The proposed algorithms are easy to be implemented in real time and costlyefficient. An extra study on networked multi-robots formation buildingalgorithm is presented in this paper. A constructive and easy-to-implementdecentralised control is proposed for a formation building of a group of randompositioned objects. Furthermore, the problem of formation building withanonymous objects is addressed. This randomised decentralised navigationalgorithm achieves the convergence to a desired configuration with probability1.

Collision free autonomous navigation and formation building for non-holonomic ground robots