Stanislav Vechet

A new function for fatigue curves characterization and its multiple merits

A new function is proposed for the description of fatigue curves in both low- and high-cycle fatigue regions, i.e. for the whole region of cycles from tensile strength to permanent fatigue limit (usually described by the Palmgren function). In each cycle region it can be simplified; in fact it changes into the Basquin function in the region of finite life and an analogy of the Stromeyer function for the high-cycle fatigue region can also be obtained. In comparison with the functions mentioned above, the new function has many advantages: it allows a better fit of experimental results, its parameters have unambiguous technical and geometrical meaning and they can be determined with higher accuracy. The function and its simplifications are also more suitable for extrapolation and interpolation of fatigue curves in low-cycle and very-high-cycle regions.

Development of energy harvesting sources for remote applications as mechatronic systems

This paper deals with a complex energy harvesting system which generates electric energy from its surroundings. The source of an ambient energy can be available in the form of solar, thermal or mechanical energy. The paper is focused on the energy harvesting from mechanical energy of vibrations. The mechatronic approach was used for development of the energy harvesting source which harvests electrical energy from ambient mechanical vibrations.

Odometry-free mobile robot localization using bearing only beacons

The paper deals with the localization of mobile robot using the bearing only beacons as the only source of sensor data. The localization is based on Extended Kaiman Filter. Derivation of localization algorithm is given together with test results for both simulation and real robot equipped with low cost sensor hardware. Beacons use infrared LEDs detected by the receiver on the robot and position estimator runs on Atmega microcontroller.

Hybrid Navigation Method for Dynamic Indoor Environment Based on Mixed Potential Fields

Navigation task for highly populated indoor environment belongs to the most difficult issues in mobile robotics. Presented paper deals with a hybrid approach which combines three methods: potential fields, Voronoi diagrams and rule based path planner. Such combination takes the best of all mentioned methods to create reliable navigation system with maximum emphasis on safety. The method was verified using real mobile robot in common environment with dynamic obstacles.

Sensor failure detection in autonomous mobile robot application

Presented paper deals with sensor failure detection and identification (FDI) in navigation task of autonomous mobile robot. Mobile robots use ultrasonic range finders to solve a collision avoidance task, which is crucial for successful navigation. When the sensory readings are invalid the robot should be able to detect such a failure and interrupt its actual movement. To solve this task, the method based on first-order Markov chain parameters estimation was developed and tested in both the simulation and the real world environment. Practical experiments were performed on autonomous mobile robot Advee.

Design of the control basis for walking gait generation based on DEDS

This contribution deals with using the hybrid control architecture for walking gait generation of the four legged robot. The main aim is to design and implement the control basis layer. Software simulation is used for validation of proposed solution.

Probabilistic Reasoning in Diagnostic Expert System for Smart Homes

We present an expert system shell suitable for smart homes application where a diagnostics or prediction functionality can be used. Presented expert system is based on probabilistic theory and decision networks, which brings natural support for uncertainty handling. Dealing with uncertainty is one of features the expert system has and since it is designed as an empty expert system it can be transformed to other domain e.g. onboard diagnostic application for mobile robots.

Determination of Optimal Local Path for Mobile Robot

The paper presents the method of finding locally optimal path with respect to the safety of the mobile robot with non-holonomic constraints. The path is represented by the polyline and circular segments. Initial path is found in the geometrical centers of the corridors to pass through and is optimized using evolutionary algorithm. The complexity of path description can be sequentially increased, allowing to further improve the quality of the path while optimization can be interrupted any time. Minimal distance to the obstacles is taken as optimality criterion.

Suppression of motion-induced vibration for a two-DoF system using state feedback control

Residual vibration control is crucial for applications in long-range precision transportation, which requires fast maneuvers with small motion-induced swings as well as low residual vibrations. To achieve this goal, vibrations resulted from structure motion must be analyzed and suppressed. A two-degree of freedom pendulum system mounted on a linear servomotor was realized to simulate the motion of high speed rest-to-rest maneuvers for developing vibration control strategies. Two feedback control schemes: i.e., loop shaping controls for SISO systems and full state feedback with observers and feedback linearization for MIMO systems were developed. The experimental results indicated that in comparison with the loop shaping control, the MIMO scheme could achieve a better performance due to its abilities for counting the coupling and compensating nonlinearities. The research results should be useful in residual vibration reduction for mechatronics applications in precision positioning.

Enhancement of Autonomous Robot Navigation via Sensor Failure Detection

Sensor Failure Detection and Identification (FDI) is a standard method in many technical applications. Presented paper describes the usage of such approach in autonomous mobile robot navigation tasks. The FDI method uses pattern matching principle based on Markov chain theory. Such approach is capable to avoid any miss-readings or sensor failures during navigation task. This method significantly improves the robustness of mobile robot navigation in crowded environment shared with people. Practical verification experiments were performed on autonomous mobile robot Advee, which is designed to safely move among people.