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Phone:
+420-22435-7284
Email:
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Position:
PhD student
Room:
E-129

 

Education:   2016 Ing. (=M.Sc.) in Cybernetics and robotics
Teaching:   Řešení problémů a hry
Research Interest:   motion planning, multi-robot monitoring and coverage
Publications:  
  1. R Pěnička, J Faigl, P Váňa and M Saska. Dubins Orienteering Problem. IEEE Robotics and Automation Letters 2(2):1210-1217, April 2017. PDF, DOI BibTeX

    @article{7847413,
    	author = "R. Pěnička and J. Faigl and P. Váňa and M. Saska",
    	journal = "IEEE Robotics and Automation Letters",
    	title = "Dubins Orienteering Problem",
    	year = 2017,
    	volume = 2,
    	number = 2,
    	pages = "1210-1217",
    	keywords = "geometry;search problems;transportation;Dubins orienteering problem;Dubins vehicle;Euclidean OP;curvature constrained vehicle;variable neighborhood search technique;Approximation algorithms;Data collection;Optimization;Planning;Traveling salesman problems;Turning;Unmanned aerial vehicles;Aerial systems: applications;motion and path planning;nonholonomic motion planning",
    	doi = "10.1109/LRA.2017.2666261",
    	issn = "2377-3766",
    	month = "April",
    	pdf = "data/papers/ral2017dop.pdf"
    }
    
  2. J Faigl, R Pěnička and G Best. Self-organizing map-based solution for the Orienteering problem with neighborhoods. In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). October 2016, 001315-001321. DOI BibTeX

    @inproceedings{7844421,
    	author = "J. Faigl and R. Pěnička and G. Best",
    	booktitle = "2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",
    	title = "Self-organizing map-based solution for the Orienteering problem with neighborhoods",
    	year = 2016,
    	pages = "001315-001321",
    	abstract = "In this paper, we address the Orienteering problem (OP) by the unsupervised learning of the self-organizing map (SOM). We propose to solve the OP with a new algorithm based on SOM for the Traveling salesman problem (TSP). Both problems are similar in finding a tour visiting the given locations; however, the OP stands to determine the most valuable tour that maximizes the rewards collected by visiting a subset of the locations while keeping the tour length under the specified travel budget. The proposed stochastic search algorithm is based on unsupervised learning of SOM and it constructs a feasible solution during each learning epoch. The reported results support feasibility of the proposed idea and show the performance is competitive with existing heuristics. Moreover, the key advantage of the proposed SOM-based approach is the ability to address the generalized OP with Neighborhoods, where rewards can be collected by traveling anywhere within the neighborhood of the locations. This problem generalization better fits data collection missions with wireless data transmission and it allows to save unnecessary travel costs to visit the given locations.",
    	keywords = "Conferences;Data collection;Heuristic algorithms;Robot sensing systems;Self-organizing feature maps;Traveling salesman problems",
    	doi = "10.1109/SMC.2016.7844421",
    	month = "Oct"
    }
    
  3. Axel Vick, Vojtech Vonasek, Robert Penicka and Jorg Kruger. Robot control as a service - Towards cloud-based motion planning and control for industrial robots. In Robot Motion and Control (RoMoCo), 2015 10th International Workshop on. July 2015, 33-39. URL PDF, DOI BibTeX

    @inproceedings{7219710,
    	author = "Vick, Axel and Vonasek, Vojtech and Penicka, Robert and Kruger, Jorg",
    	booktitle = "Robot Motion and Control (RoMoCo), 2015 10th International Workshop on",
    	title = "Robot control as a service - Towards cloud-based motion planning and control for industrial robots",
    	year = 2015,
    	pages = "33-39",
    	keywords = "Collision avoidance;Interpolation;Planning;Robot kinematics;Robot sensing systems;Service robots",
    	doi = "10.1109/RoMoCo.2015.7219710",
    	month = "July",
    	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7219710",
    	pdf = "data/papers/romoco2015-rcaas.pdf"
    }