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Provedení rešeršní studie v oblasti metod simultánní lokalizace a mapování.
Gärtner, Jan ; Marada, Tomáš (oponent) ; Věchet, Stanislav (vedoucí práce)
Tato práce se zabývá metodami simultánní lokalizace a mapování používanými v aplikacích mobilní robotiky ve světě. Cílem této práce je popsat existující a používané metody simultánní lokalizace a mapování. V první části je uvedeno rozdělení a popis jednotlivých podproblémů simultánní lokalizace a mapování. V druhé části jsou popsány konkrétní metody simultánní lokalizace a mapování. Třetí část se věnuje praktickým aplikacím metod simultánní lokalizace a mapování používaných v robotických úlohách ve světě. Poslední část je věnována robotickým aplikacím v rámci FSI VUT v Brně a použitelnosti jednotlivých metod pro tyto aplikace.
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Covering the Working Space of Mobile Robot
Krejsa, Jiří ; Věchet, Stanislav
Equally distributed covering of working space is essential in some mobile robot applications, such as presentation robotics or security robot patrol. This paper explores a method for such covering based on rapidly exploring random trees (RRT) algorithm. RRTs can cover the working space close to completeness while uncovered areas are quickly reduced. The algorithm can be modified to emphasize certain areas of interest by appropriately generating corresponding goals. Method performance is compared to random walk in simulation experiments.
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Multiple Indoor Robot Localization Using Infrared Beacons
Krejsa, Jiří ; Věchet, Stanislav ; Chen, K.-S.
Mobile robot localization based on active artificial landmarks is well established robust technique in indoor mobile robotics. This paper explores the extension of the method to multiple robot localization, with the key idea of using the robots themselves as the artificial landmarks, supplying other robots in the group with its estimate of position. The method uses nonlinear version of Kalman filter for determination of position estimate in 2D space, x-y coordinates and angle with respect to global coordinate system, with the estimate represented by mean values and corresponding covariances. Simulation results based on model well verified with the real system suggest that while only small reduction of number of fixed active landmarks can be achieved, the main advantage of the method is in increased robustness of localization technique with respect to obscured landmarks fields of view.
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Mobile Robot Tracking Using Image Processing
Krejsa, Jiří ; Věchet, Stanislav ; Ripel, T.
During the evaluation of autonomous mobile robot navigation routines the determination of true robot position on its track is essential. The paper presents simple yet reliable method of tracking robot position using processing of images acquired from the devices positioned above the operation space. The method consists of two steps for each image: detection of the robot in image space and transfer of its coordinates to operation space.
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Concurrent mapping and localization based on potential fields
Věchet, Stanislav ; Krejsa, Jiří
Presented paper deals with Concurrent Mapping and Localization as a method to build the local map for the autonomous mobile robot. Building accurate local map is necessary for the successful navigation through the crowded environment densely populated with dynamic obstacles. The occupancy grid mapping algorithm was used due to the high uncertainty in the measurements of dynamic obstacles. As the occupancy grid algorithm is of probabilistic nature the implementation is straightforward and is also capable to generate the results in real-time.
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Mobile robot motion planner via neural network
Krejsa, Jiří ; Věchet, Stanislav
Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the human can still do a better job, therefore it would be advantageous to create a planner based on data gathered from the robot simulation when humans do the planning. The paper presents the method of using the neural network to transfer the previously gained knowledge into the machine learning based planner. In particular the neural network task is to mimic the planner based on finite state machine. The tests proved that neural network can successfully learn to navigate in constrained environment.
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Experimental Determination of Human Arm Force/Elbow Joint Angle Relation
Krejsa, Jiří ; Zezula, M. ; Věchet, Stanislav
The achievable force at the end of human forearm depends on the forearm position. The actual value of this force is one of the most important variables affecting the design of the motorized splint, but reliable data are hard to find. Sophisticated measuring device was constructed to determine this force. The force is measured during the movement of the forearm, as such method yields better results than static measurement. The trajectory of movement is enforced by the measuring device, so the influence of the subject on the trajectory is eliminated.
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Rychlá metoda srovnávání skenů pro lokalizaci mobilního robotu
Krejsa, Jiří ; Věchet, Stanislav
Příspěvek je zaměřen na rychlou metodu která používá postupné skeny prostředí mobilního robota proximitními senzory k určení polohy a orientace robotu a k tvorbě lokální mapy. Prostředí je předpokládáno neznámé. Metoda založená na srovnávání potenciálových polí skenů které poskytuje míru shodnosti skenů je kombinována s gradientní metodou k získání odpovídají shody dvou skenů v rozumném čase. Příspěvek obsahuje testy na robustnost metody vůči šumu v senzorech.
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