Stabilization and control of teams of relatively-localized micro aerial vehicles in high obstacle density areas 

 
 
In the proposed project, the task of stabilization and coordination of a team of Micro Aerial Vehicles (MAV) autonomously flying in a GPS-denied environment with obstacles will be investigated. The proposed theory and methodology will be based on a visual relative localization of MAVs within the team, which relies strictly on onboard sensors and computational resources. Stabilization and coordination of particular MAVs will be realized using techniques of model predictive control with integrated ability of fast obstacle avoidance. Within the project, conditions of group stability will be analyzed, with a focus on situations in which direct visibility, and therefore also relative localization between MAVs, is interrupted by an obstacle. In addition, influence of the desired shape of the group (relative positions of MAVs) on measurement of relative localization uncertainty and on system stability during flying through areas with obstacles will be studied. The resulting system for MAV group stabilization will be experimentally verified in specified multi-MAV scenarios.
 
The aim of the project is to theoretically and experimentally analyse stability of teams of micro aerial vehicles (MAVs) flying through areas with high obstacle density and to study influence of required relative positions of MAVs on stability of onboard model predictive control and coordination.
 
 
 
Publications:
  1. R Pěnička, J Faigl, P Váňa and M Saska. Dubins orienteering problem with neighborhoods. In 2017 International Conference on Unmanned Aircraft Systems (ICUAS). June 2017, 1555-1562. DOI BibTeX

    @inproceedings{7991350,
    	author = "R. Pěnička and J. Faigl and P. Váňa and M. Saska",
    	booktitle = "2017 International Conference on Unmanned Aircraft Systems (ICUAS)",
    	title = "Dubins orienteering problem with neighborhoods",
    	year = 2017,
    	pages = "1555-1562",
    	abstract = "In this paper, we address the Dubins Orienteering Problem with Neighborhoods (DOPN) a novel problem derived from the regular Orienteering Problem (OP). In the OP, one tries to find a maximal reward collecting path through a subset of given target locations, each with associated reward, such that the resulting path length does not exceed the specified travel budget. The Dubins Orienteering Problem (DOP) requires the reward collecting path to satisfy the curvature-constrained model of the Dubins vehicle while reaching precise positions of the target locations. In the newly introduced DOPN, the resulting path also respects the curvature constrained Dubins vehicle as in the DOP; however, the reward can be collected within a close distant neighborhood of the target locations. The studied problem is inspired by data collection scenarios for an Unmanned Aerial Vehicle (UAV), that can be modeled as the Dubins vehicle. Furthermore, the DOPN is a useful problem formulation of data collection scenarios for a UAV with the limited travel budget due to battery discharge and in scenarios where the sensoric data can be collected from a proximity of each target location. The proposed solution of the DOPN is based on the Variable Neighborhood Search method, and the presented computational results in the OP benchmarks support feasibility of the proposed approach.",
    	keywords = "Batteries;Data collection;Discharges (electric);Fault diagnosis;Traveling salesman problems;Turning;Unmanned aerial vehicles",
    	doi = "10.1109/ICUAS.2017.7991350",
    	month = "June"
    }
    
  2. 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"
    }
    
  3. Tomas Baca, Peter Stepan and Martin Saska. Autonomous Landing On A Moving Car With Unmanned Aerial Vehicle. In ECMR. 2017. BibTeX

    @inproceedings{backa2017autonomous,
    	author = "Tomas Baca and Peter Stepan and Martin Saska",
    	title = "Autonomous Landing On A Moving Car With Unmanned Aerial Vehicle",
    	booktitle = "ECMR",
    	year = 2017
    }
    
  4. R Pěnička, M Saska, C Reymann and S Lacroix. Reactive Dubins Traveling Salesman Problem for Replanning of Information Gathering by UAVs. In ECMR. 2017. URL BibTeX

    @inproceedings{penicka_ecmr_rdtsp,
    	author = "R. Pěnička and M. Saska and C. Reymann and S. Lacroix",
    	title = "Reactive Dubins Traveling Salesman Problem for Replanning of Information Gathering by UAVs",
    	booktitle = "ECMR",
    	year = 2017,
    	url = "http://mrs.felk.cvut.cz/ecmr17rdtsp"
    }
    
  5. Daniel Brandtner and Martin Saska. Coherent swarming of unmanned micro aerial vehicles with minimum computational and communication requirements. In ECMR. 2017. BibTeX

    @inproceedings{brandtner2017coherent,
    	author = "Daniel Brandtner and Martin Saska",
    	title = "Coherent swarming of unmanned micro aerial vehicles with minimum computational and communication requirements",
    	booktitle = "ECMR",
    	year = 2017
    }
    
  6. Martin Saska, Vit Kratky, Vojtech Spurny and Tomas Baca. Documentation of Dark Areas of Large Historical Buildings by a Formation of Unmanned Aerial Vehicles using Model Predictive Control. In ETFA. 2017. BibTeX

    @inproceedings{saska2017documentation,
    	author = "Martin Saska and Vit Kratky and Vojtech Spurny and Tomas Baca",
    	title = "Documentation of Dark Areas of Large Historical Buildings by a Formation of Unmanned Aerial Vehicles using Model Predictive Control",
    	booktitle = "ETFA",
    	year = 2017
    }
    
  7. Martin Saska. Large sensors with adaptive shape realised by self-stabilised compact groups of micro aerial vehicles. In ISRR. 2017. BibTeX

    @inproceedings{saska2017large,
    	author = "Martin Saska",
    	title = "Large sensors with adaptive shape realised by self-stabilised compact groups of micro aerial vehicles",
    	booktitle = "ISRR",
    	year = 2017
    }