Abstract
This study presents an effective navigation archite cture that combines ‘go-to-goal’, ‘avoid-obstacle’ and ‘follow-wall’ controllers into a full navigation sy stem. A MATLAB robot simulator is used to implement this navigation control algorithm. The robot in the simulator moves to a goal in the presence of conve x and non-convex obstacles. Experiments are carried out u sing a ground mobile robot, Dr Robot X80SV, in a typical office environment to verify successful imp lementation of the navigation architecture algorith m programmed in MATLAB. The research paper also demonstrates algorithms to achieve tasks such as ‘move to a point’, ‘move to a pose’, ‘follow a line’, ‘mo ve in a circle’ and ‘avoid obstacles’. These contro l algorithms are simulated using Simulink models.
Highlights
Robots (WMRs) are increasingly present in industrial and service robotics, when flexible motionThe field of mobile robot control has attracted considerable attention of researchers in the areas of robotics and autonomous systems in the past decades
This study presents an effective navigation architecture that combines ‘go-to-goal’, ‘avoid-obstacle’ and ‘follow-wall’ controllers into a full navigation system
Experiments are carried out using a ground mobile robot, Dr Robot X80SV, in a typical office environment to verify successful implementation of the navigation architecture algorithm programmed in MATLAB
Summary
Robots (WMRs) are increasingly present in industrial and service robotics, when flexible motionThe field of mobile robot control has attracted considerable attention of researchers in the areas of robotics and autonomous systems in the past decades. One of the goals in the field of mobile robotics is the development of mobile platforms that robustly operate in populated environments and offer various services to humans. Autonomous mobile robots need to be equipped with appropriate control systems to achieve the goals. Such control systems are supposed to have navigation control algorithms that will make mobile robots successfully ‘move to a point’, ‘move to a pose’, ‘follow a path’, ‘follow a wall’ and ‘avoid obstacles (stationary or moving)’. Several mobility configurations (wheel number and type, their location and actuation and singleor multi-body vehicle structure) can be found in different applications (De Luca et al, 2001). The most common for single-body robots are differential drive and synchro drive (both kinematically equivalent to a unicycle), tricycle or car-like drive and omnidirectional steering (De Luca et al, 2001)
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