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This article is concerned with autonomous planning of diverse cooperative robot actions. In this work complex cooperative actions are realized based upon the intelligent composite motion control, which is a learning methodology for intelligent robots that gradually realize complex actions from fundamental motions. For efficient construction of action intelligence multi-stage genetic algorithm, MGA,...
As the applications of mobile robot teams become more complex, the impracticality of designing custom solutions is becoming increasingly obvious. A new approach to control system design is required to facilitate the development of modular and scalable systems. Control ad libitum is an approach that decouples the software and hardware design of robot teams, allowing the system to adapt to changing...
Autonomous mobile robots must accomplish tasks in unknown and noisy environments. In this context, learning robot behaviors in an imitation based approach would be desirable in the perspective of service robotics as well as of learning robots. In this work, we use reservoir computing (RC) for learning robot behaviors by demonstration. In RC, a randomly generated recurrent neural network, the reservoir,...
To meet the necessity of handling environmental uncertainties of mobile robots, we proposed an efficient exploration strategy to gather information, called entropy sweeper. To do so, we utilized the entropy distribution and the utility function to determine which positions have more uncertainties. Proposed strategy is divided into two phases: the learning phase and the action phase. In general, uncertainties...
The conventional Q-learning algorithm is described by a finite number of discretized states and discretized actions. When the system is represented in continuous domain, this may cause an abrupt transition of action as the state rapidly changes. To avoid this abrupt transition of action, the learning system requires fine-tuned states. However, the learning time significantly increases and the system...
This paper presents the application of genetic algorithm (ga) and ant colony optimization (ACO) algorithm for robot path planning (RPP) in global static environment. Both algorithms were applied within global maps that consist of different number of free space nodes. These nodes generally represent the free space extracted from the robot map. Performances between both algorithms were compared and...
In this paper, we introduce the experimental test platform for bio-insect and artificial robot interaction based on distributed systems (BRIDS). The main architecture of the BRIDS was reported in and simulation results were introduced. One of the most challenging problems of BRIDS is that a bio-insect does not usually react to actuation. When we try to stimulate the bio-insect for our purpose, its...
The trajectory tracking control problem of nonholonomic mobile robots with parameter uncertainties has been analyzed. The kinematics and dynamical models of mobile robots are taken into account, the control rule based on the kinematics model is taken as desired virtual control, and the adaptive sliding mode controller is designed, as the controller take into account both kinematics and dynamical model,...
Pet has been serving as an emotional companion to people. However, nowadays it is common that people are too busy to take care of their pet due to everyday work. This research is to see the possibility that robot can replace the role of taking care of pets on behalf of their owner and the conventional human-robot interaction (HRI) can be extended to the interaction of robots and animals. In this paper,...
Robocup rescue simulation system is a suitable test-bed for test and evaluation of multi-agent system's related ideas and techniques. Hence, the world robocup competitions are held each year and the used ideas and techniques are evaluated in the form of different teams. In rescue simulation system, at the start of simulation, police agents should search and explore the earthquake area and open the...
This article introduces the development of a fast 3D active vision system, and a new concept based on space decomposition into virtual planes to support 3D real time obstacle detection during the navigation mission of autonomous mobile robots. This system uses the richness and the strength of the vision while reducing the data load, and computational cost by encoding coarsely the working space using...
We present a novel control architecture for execution of multiple tasks simultaneously. Traditionally, the task control architecture of a service robot has been focused on executing one task at a time. This has mainly been due to the history of mobility being the only function and tasks being so simple that just one or two abstract commands have been sufficient. During the last decade, these requirements...
This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with...
In this study, we discussed human recognition method for the trajectory tracking. Visual perception is very important to realize the feature extraction from the time series of images, but it is very difficult to perform the object tracking. We classified errors occurring in the throwing; errors caused by internal factors and errors caused by external factors. At first, we propose a theoretical method...
Autonomous robotic excavation has often been limited to a single robotic platform using a specified excavation vehicle. This paper presents a novel method for developing scalable controllers for use in multirobot scenarios and that do not require human defined operations scripts nor extensive modeling of the kinematics and dynamics of the excavation vehicles. Furthermore, the control system does not...
Path planning together with the tuning and determination of controller parameters are major concerns in omnidirectional mobile robots. Defining appropriate controller parameters in acceleration and deceleration to reach far and near target points without slippage is one of critical issues since some troubles due to unregulated velocities may greatly affect the ability of robot for the specified path...
This paper addresses a novel approach to the solution of the simultaneous localization and mapping (SLAM) problem bared on a neuro evolutionary optimization (NeoSLAM) method. The proposed algorithm first casts SLAM as a global optimization problem using the cost function which represents the quality of robot pose trajectory and the feature positions in world coordinate frame. In our algorithm, the...
Experimental issues arise when scientists attempt to directly study emergent behaviour brought on by the evolutionary process. Recently, algorithms that simulate artificial evolution in robotic societies have been used to circumvent such issues. This study attempts to investigate and interpret emergent signals used by artificial agents when evolved through a simple genetic algorithm setup. A multiagent...
Autonomous robotic systems and intelligent artificial agents' capability have advanced dramatically. Since the intelligent artificial agents have been developing more autonomous and human-like, the capability of them to make moral decisions becomes an important issue. In this work we developed an artificial neutral network which considered various effective factors for ethical assessment of an action...
In order to realize intelligent agent such as autonomous mobile robots, reinforcement learning is one of the necessary techniques in behavior control system. However, applying the reinforcement learning to actual sized problem, the ??curse of dimensionality?? problem in partition of sensory states should be avoided maintaining computational efficiency. In multi-agent reinforcement learning, the problem...
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