Crawler robots are popular in tasks of urban search and rescue. Because of using tracks most of these robots have good traversability on rough terrains. For creating and testing these abilities and crawler robot itself often used simulators, which could help to reconstruct most of the conditions and environment without any difficulties. And this is a reason why most of the robots must have its simulation model.In this paper, we present a fully equipped and moving model of tracked robot Servosila "Engineer". It contains all of the sensors that used a real robot with the ability to get information from them via ROS topics through all the time of the simulation. Also, it has similar to real robot control elements, physic characteristics and useful crawler simulation.

A simulator is a software application that allows imitating an experimental environment and controlling a process or an instrument. Projects in human-robot interaction (HRI) field face different challenges during real world experiments, which include improper robot behavior, mistakes in an algorithm logic, software and hardware failures, and generic lay participants on a user side. Simulators could help to avoid a number of problems that researchers would definitely face within real world experiments at algorithms' testing stage. This study presents an experimental validation in Gazebo simulator and real-world experiments for English language lessons scenarios with a small size humanoid Robotis DARwin OP2. We investigated advantages of using Gazebo simulator in constructing modular generic HRI blocks and global HRI scenarios in order to optimize a humanoid robot assisted process of studying English. The simulator saved a significant amount of efforts and time at preparatory stages, allowing robot programmers and HRI developers to obtain a quick feedback from users and their requirements for necessary adjustments.

This work discloses the dynamic control model of a hexapod robot with tripod-based walking gait. The proposed walking model is based on the Klann linkage and three main actuators to provide quasi-omnidirectional mobility. The reduced number of actuators preserve holonomy as similar as popular 18-servo hyper-redundant hexapods (three servos per leg). This work proposes two-drive differential control, one drive per lateral triplet of legs. Each triplet is synchronized in speed with different angle phase of rotation. The six limbs are synchronized with bidirectional yaw motion with the third actuator. Quasiomnidirectional mobility was achieved and controlled by a dynamic control law that governs the robots mechanisms motion. Kinematic and dynamic results are validated through numerical simulations using a tripod gait.

There is a problem associated with various natural and man-made emergencies. The consequences of which can be colossal destruction in densely populated territories. Therefore, USAR teams, which include rescue robots, need to act quickly. However, due to the unpredictability of the situation, rescuers are faced with a number of difficulties due to which expensive equipment can suffer. To prevent the latter and optimize the work of robots, it is necessary to conduct testing in an environment close to reality. For many reasons, this cannot be done in real life, so there is a need to recreate the danger situations in format USAR in a simulation environment, designed to develop algorithms for the interaction of robots with a simulated environment.

Ubiquitous nature of information determines continuous decision making always based on its stream coming from the environment, not only in the human, but also in the animal world. Communication between the users of information system is a fundamental concept for acquiring, showing, spreading, sharing and constantly increasing the knowledge about the circumstances under which they are in need to make a move all alone as well as while working in groups. In this paper, we review information stream-based systems on amount of information acceptable to facilitate the process of decision making, also in multilingual settings. We analyze the information system objects and the resource management cycle. In addition, methodology of data mining in natural language is investigated. Multilingual information flow between the users is specific while analyzing from the contextual perspective, when the range of information system applications becomes extended to international cooperation.

In particular, service robotics is strongly tided to highly accurate navigational tasks where pathway tracking is a practice commonly carried out through control algorithms. This study proposes theoretical non-linear pathways presented as kth-degree polynomials as model references. Our proposal establishes a proportional control with a variable model reference at the level of second order derivatives to which the robot's motion is adapted on-line. The robot's fixed frame Cartesian trajectory model is inversely transformed to wheels' angular acceleration components, which are the reference models. Although, our proposal may be applied to any type of wheeled robot's kinematic structure, we are presenting an example of two active wheels with differential velocity modality. Obtained results raised from successful experimental practice and numerical simulations as well, which depict the capability of the proposed model control.

One of the key benefits of reconfigurable legged robots is their ability to move in a non-continuous way enabling it to provide better mobility over rough and irregular terrains. Legged robots should maintain it stability during rest and motion with minimum number of legs while maintaining its functionality during various gait generation and its resultant application. In this paper we have presented a stability analysis for reconfigurable Klann mechanism based quadruped by changing leg arrangement for six useful gait cycles. The platform stability based on COG (Center of Gravity) for this six useful gait cycles are validated through simulated results.

We present a visual based approach for reactive autonomous navigation of an underwater vehicle. In particular, we are interested in the exploration and continuous monitoring of coral reefs in order to diagnose disease or physical damage. An autonomous underwater vehicle needs to decide in real time the best route while avoiding collisions with fragile marine life and structure. We have opted to use only visual information as input. We have improved the Simple Linear Iterative Cluster algorithm which, together with a simple nearest neighbor classifier, robustly segment and classify objects from water in a fast and efficient way, even in poor visibility conditions. From the resulting classification and the current robot's direction and orientation, the next possible free-collision route can be estimated. This is achieved by grouping together neighboring water superpixels (considered as “regions of interest”). Finally, we use a model-free robust control scheme that allows the robot to autonomously navigate through the free-collision routes obtained in the first step. The experimental results, both in simulations and in practice, show the effectiveness of the proposed navigation system.