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Implementation of autonomus navigation algorithm

David Ezenwoye


Autonomous navigation algorithm portals the implementation of numerous navigational function on a robot to enable it move from a particular location to another. In this thesis an experimented task will be carry out on a simulator (such as a robotic virtual environment) and consequently be implemented on a real robot in a real environment. Motion planning problem for mobile robot is typically formulated as follows1: given a robot and the description of the environment, plan a path of the robot between two specified locations, which is collision free and satisfies optimization criteria. Primarily, experiments on the robot will be both on a simulator and a real environment to read various constructed metric and topological maps. Also the experiment will include the building of a simple map using various mapping tools like SLAM, which the map will represent an exact replication of a real world, and also finding an optimal path from a starting location to a goal point. I concentrated on the navigating techniques of the robot which will enable the robot to read sensor information about the environment and use them in the construction of path planning, additionally the robot also navigates and avoid obstacles. Firstly, the algorithm structure for navigation will be presented. Following with a presented new framework that is able to process maps and compute paths. The experiments performed using simulated and real environments for the evaluation purpose will be shown. Implementation of the algorithm to find the shortest path to the robot final destination avoiding various obstacles will be discussed. A generalized experimental performance showed in the Laboratory of Intelligent Mobile Systems, Institute of Automatic Control and Robotics, Warsaw University of Technology. Lastly, subtasks will be categorize into three stages, an algorithm to handle navigation and connectivity, an algorithm to handle obstacle avoidance and an algorithm to solve finding an optimal path from a starting point to the goal point. There algorithms for finding optimal path would be analyzed and conclusively one will be chosen, example of these algorithm are, wavefront algorithm, A* algorithm, greedy first search algorithm, the algorithms for constructing roadmaps connectivity and obstacle avoidances will be in detailed in subsequent sectio
Record ID
Diploma type
Master of Science
David Ezenwoye (FPAE) David Ezenwoye,, Faculty of Power and Aeronautical Engineering (FPAE)
Andrzej Masłowski (FM/IACR) Andrzej Masłowski,, The Institute of Automatic Control and Robotics (FM/IACR)Faculty of Mechatronics (FM)
Certifying unit
Faculty of Power and Aeronautical Engineering (FPAE)
Affiliation unit
The Institute of Automatic Control and Robotics (FM/IACR)
Study subject / specialization
, Automatyka i Robotyka (Automatic Control and Robotics)
(en) English
Defense Date
Issue date (year)
Internal identifier
Andrzej Masłowski (FM/IACR) Andrzej Masłowski,, The Institute of Automatic Control and Robotics (FM/IACR)Faculty of Mechatronics (FM) Janusz Będkowski (FM/IACR) Janusz Będkowski,, The Institute of Automatic Control and Robotics (FM/IACR)Faculty of Mechatronics (FM)
Keywords in Polish
Keywords in English
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    Ezenwoye David.23384.Meil.pdf
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