Jan Chudoba

SyRoTek—Distance Teaching of Mobile Robotics

E-learning is a modern and effective approach for training in various areas and at different levels of education. This paper gives an overview of SyRoTek, an e-learning platform for mobile robotics, artificial intelligence, control engineering, and related domains. SyRoTek provides remote access to a set of fully autonomous mobile robots placed in a restricted area with dynamically reconfigurable obstacles, which enables solving a huge variety of problems. A user is able to control the robots in real time by their own developed algorithms as well as being able to analyze gathered data and observe activity of the robots by provided interfaces. The system is currently used for education at the Czech Technical University in Prague, Prague, Czech Republic, and at the University of Buenos Aires, Buenos, Aires, Argentina, and it is freely accessible to other institutions. In addition to the system overview, this paper presents the experience gained from the actual deployment of the system in teaching activities.

Low-cost embedded system for relative localization in robotic swarms

In this paper, we present a small, light-weight, low-cost, fast and reliable system designed to satisfy requirements of relative localization within a swarm of micro aerial vehicles. The core of the proposed solution is based on off-the-shelf components consisting of the Caspa camera module and Gumstix Overo board accompanied by a developed efficient image processing method for detecting black and white circular patterns. Although the idea of the roundel recognition is simple, the developed system exhibits reliable and fast estimation of the relative position of the pattern up to 30 fps using the full resolution of the Caspa camera. Thus, the system is suited to meet requirements for a vision based stabilization of the robotic swarm. The intent of this paper is to present the developed system as an enabling technology for various robotic tasks.

Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance

An algorithm for autonomous deployment of groups of Micro Aerial Vehicles (MAVs) in the cooperative surveillance task is presented in this paper. The algorithm enables to find a proper distributions of all MAVs in surveillance locations together with feasible and collision free trajectories from their initial position. The solution of the MAV-group deployment satisfies motion constraints of MAVs, environment constraints (non-fly zones) and constraints imposed by a visual onboard relative localization. The onboard relative localization, which is used for stabilization of the group flying in a compact formation, acts as an enabling technique for utilization of MAVs in situations where an external local system is not available or lacks the sufficient precision.

System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

A complex system for control of swarms of micro aerial vehicles (MAV), in literature also called as unmanned aerial vehicles (UAV) or unmanned aerial systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possibility of self-stabilization of multi-MAV groups without an external global positioning system. This approach enables the deployment of MAV swarms outside laboratory conditions, and it may be considered an enabling technique for utilizing fleets of MAVs in real-world scenarios. The proposed visual-based stabilization approach has been designed for numerous different multi-UAV robotic applications (leader-follower UAV formation stabilization, UAV swarm stabilization and deployment in surveillance scenarios, cooperative UAV sensory measurement) in this paper. Deployment of the system in real-world scenarios truthfully verifies its operational constraints, given by limited onboard sensing suites and processing capabilities. The performance of the presented approach (MAV control, motion planning, MAV stabilization, and trajectory planning) in multi-MAV applications has been validated by experimental results in indoor as well as in challenging outdoor environments (e.g., in windy conditions and in a former pit mine).

Swarm Distribution and Deployment for Cooperative Surveillance by Micro-Aerial Vehicles

The task of cooperative surveillance of pre-selected Areas of Interest (AoI) in outdoor environments by groups of closely cooperating Micro Aerial Vehicles (MAVs) is tackled in this paper. In the cooperative surveillance mission, finding distributions of the MAVs in the environment to properly cover the AoIs and finding feasible trajectories to reach the obtained surveillance locations from the initial depot are crucial tasks that have to be fulfilled. In addition, motion constraints of the employed MAVs, environment constraints (e.g. non-fly zones), and constraints imposed by localization of members of the groups need to be satisfied in the planning process. We formulate the task of cooperative surveillance as a single high-dimensional optimization problem to be able to integrate all these requirements. Due to numerous constraints that have to be satisfied, we propose to solve the problem using an evolutionary-based optimization technique. An important aspect of the proposed method is that the cooperating MAVs are localized relatively to each other, rather than using a global localization system. This increases robustness of the system and its deploy-ability in scenarios, in which compact shapes of the MAV group with short relative distances are required.

A Control System for Multi-Robotic Communities

This paper describes a design, development and experience with an universal multi-robotic robot control system. The overall message-driven system concept is introduced together with its open modular architecture. Besides the description of functionalities of basic modules, the approach to the system configuration and hardware abstraction layer is discussed. The control system allows to manage different types of robots in one team, whereas each team member is able to share and interchange any information with other team members. Since a lot of robotic tasks are computationally intensive and cannot be computed onboard, the system allows to distribute selected subtasks among remote computers. The system has been designed as a test-bed for research of new algorithms from an area of cooperative robotics.

Localization and stabilization of micro aerial vehicles based on visual features tracking

This article presents a method for long-term autonomous micro-aerial vehicle (MAV) localization and position stabilization. The proposed method extends MAV proprietary stabilization based on inertial sensor or optical flow processing, without use of an external positioning system. The method extracts visual features from the images captured by a down-looking camera mounted under the MAV and matching these to previously observed features. Due to its precision and reliability, the method is well suited for stabilization of MAVs acting in closely cooperating compact teams with small mutual distances between team members. Performance of the proposed method is demonstrated by experiments on a quad-copter equipped with all necessary sensors and computers for the autonomous operation.

Exploration and Mapping Technique Suited for Visual-features Based Localization of MAVs

An approach for long term localization, stabilization, and navigation of micro-aerial vehicles (MAVs) in unknown environment is presented in this paper. The proposed method relies strictly on onboard sensors of employed MAVs and does not require any external positioning system. The core of the method consists in extraction of information from pictures consequently captured using a camera carried by the particular MAV. Visual features are obtained from images of the surface under the MAV, and stored into a map that is represented by these features. The position of the MAV is then obtained through matching with previously stored features. An important part of the proposed system is a novel approach for exploration and mapping of the workspace of robots. This method enables efficient exploring of the unknown environment, while keeping the iteratively built map of features consistent. The proposed algorithm is suitable for mapping of surfaces, both outdoor and indoor, with various density of the image features. The sufficient precision and long term persistence of the method allows its utilization for stabilization of large MAV groups that work in formations with small relative distances between particular vehicles. Numerous experiments with quadrotor helicopters and various numerical simulations have been realized for verification of the entire system and its components.

A Mobile Robot for Small Object Handling

The aim of this paper is to present an intelligent autonomous robot capable of small object manipulation. The design of the robot is influenced mainly by the rules of EUROBOT 09 competition. In this challenge, two robots pick up objects scattered on a planar rectangular playfield and use these elements to build models of Hellenistic temples. This paper describes the robot hardware, i.e. electro-mechanics of the drive, chassis and manipulator, as well as the software, i.e. localization, collision avoidance, motion control and planning algorithms.

Practical Applications and Experiments with the SyRoTek Platform

SyRoTek is a platform for distant teaching and experimentation in robotics and related fields, which provides remote access to a group of thirteen fully autonomous mobile robots equipped with standard robotic sensors operating in the Arena – a restricted area with a set of fixed and retractable obstacles. Users of the system are able to control the robots real-time by their own developed algorithms and process and analyse data gathered with robots’ sensors. The SyRoTek is after several years of development and operation a technically mature system providing all functionalities enabling and sweeten a whole development process: interfaces to robotic frameworks (namely ROS: Robot Operating System and Player/Stage), simulation environment based on Stage, on-line and off-line visualization of the current state of the Arena and the robots, web interface, tutorials and documentation, etc. Thanks to operation in 24/7 mode and easy interchangeability of the robots, the system is an ideal tool for performing a huge number of long-term and repeating multi-robot experiments.