Line following robot with real–time viterbi Track–Before–Detect algorithm

Line following robots are applied in numerous application areas. High reliability of the line estimation could be obtained by the application of Track–Before–Detect algorithms, like Viterbi algorithm. The hardware and software of the robot are shown in the paper. Real–time constraint are discussed in this paper, related to the constructed robot. The obtained results shows the possibilities of tracking the single line using Raspberry Pi v.2 and Linux operating system. Streszczenie. Roboty śledzące linie znajdują zastoswania w wielu miejscach. Dużą niezawodność estymacji można osiągnąć stosując algorytmy TBD w tym Algorytm Viterbiego. W pracy pokazana część sprzętową i programową robota. Ograniczenia czasu rzeczywistego są poruszane w odniesieniu do robota. Pokazano, że można śledzić linię dzięki układowi Raspberry Pi v.2 i systemowi operacyjnemu Linux. (Robot Line following z algorytmem czasu rzeczywistego TBD)

[1]  Przemyslaw Mazurek.  Directional Filter and the Viterbi Algorithm for Line Following Robots , 2014, ICCVG.

[2]  Przemyslaw Mazurek,et al.  Code reordering using local random extraction and insertion (LREI) operator for GPGPU-based track-before-detect systems , 2012, Soft Computing.

[3]  R. Rangayyan.  Biomedical Image Analysis , 2004 .

[4]  M. H. Marhaban,et al.  Vision-based system for line following mobile robot , 2009, 2009 IEEE Symposium on Industrial Electronics & Applications.

[5]  Saeid Nahavandi,et al.  OzTug mobile robot for manufacturing transportation , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[6]  Przemyslaw Mazurek,et al.  Tracklet-Based Viterbi Track-Before-Detect Algorithm for Line Following Robots , 2015, CORES.

[7]  Van Nostrand,et al.  Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm , 1967 .

[8]  Przemyslaw Mazurek.  Line estimation using the Viterbi algorithm and track-before-detect approach for line following mobile robots , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).

[9]  Przemyslaw Mazurek.  Viterbi Algorithm for Noise Line Following Robots , 2014, IP&C.

[10]  P. K. Chaturvedi,et al.  Communication Systems , 2002, IFIP — The International Federation for Information Processing.

[11]  P. Mazurek.  Optimization of Bayesian Track-Before-Detect algorithms for GPGPUs Implementations , 2010 .

[12]  Jiann-Shiou Yang,et al.  A lane departure warning system based on the integration of the optical flow and hough transform methods , 2013, 2013 10th IEEE International Conference on Control and Automation (ICCA).

[13]  Scott T. Acton,et al.  Biomedical Image Analysis: Tracking , 2006, Biomedical Image Analysis: Tracking.

[14]  Krzysztof Okarma,et al.  A Fast Image Analysis Technique for the Line Tracking Robots , 2010, ICAISC.

[15]  Lawrence D. Stone,et al.  Bayesian Multiple Target Tracking , 1999 .

[16]  Albert-Jan Baerveldt,et al.  A vision based row-following system for agricultural field machinery , 2005 .

[17]  Ilknur Colak,et al.  Evolving a Line Following Robot to use in shopping centers for entertainment , 2009, 2009 35th Annual Conference of IEEE Industrial Electronics.