International Journal of Advanced Robotic Systems
Volume 1 Number 3 September 2004 |
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots, Page 141-148 Abstract: This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Técnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams.
Dynamic Modelling and Adaptive Traction Control for Mobile Robots, Page 149-154 Abstract: Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.
Robots Social Embodiment in Autonomous Mobile Robotics, Page 155-170 Abstract: This work aims at demonstrating the inherent advantages of embracing a strong notion of social embodiment in designing a real-world robot control architecture with explicit “intelligent” social behaviour between a collective of robots. It develops the current thinking on embodiment beyond the physical by demonstrating the importance of social embodiment. A social framework develops the fundamental social attributes found when more than one robot co-inhabit a physical space. The social metaphors of identity, character, stereotypes and roles are presented and implemented within a real-world social robot paradigm in order to facilitate the realisation of explicit social goals.
A People-Localization Method for Multi-Robot Systems: First Approach for Guiding-Tours, Page 171-182 Abstract: Throughout this article we present a methodology to localize multiple people in a group by a multi-robot system (MRS). The aim of the MRS is to conduct people through hallways in indoors as a guided-tour service task. However, further than guidance process, we detail a method for humans’ localization by sharing distributed sensor data arising from the team of robots instrumented with stereo vision. The robustness of the method is presented, and by matching the real environment against the computed results, error in human localization is showed as well. As a first approach of the entire MRS goal, this paper explains from a task approach the way for environment ranging, spatial noise filtering, distributed sensor data fusion and clustering based segmentation. Likewise, through the paper experimental results are shown to verify the feasibility of the method.
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL), Page 183-190 Abstract: An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot’s pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot’s pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL). Experiments have been carried out to prove the efficiency of the new localization algorithm.
Design and Development of a Comprehensive Omni directional Soccer Player Robot, Page 191-200 Abstract: Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, omni directional navigation system, omni-vision system and omni-kick mechanism in such soccer player robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, i.e. a comprehensive omni directional soccer player robot. Such a robot can respond more quickly and it would be capable for more sophisticated behaviors such as ball passing or goal keeping. This paper has tried to focus on description of areas such as omni directional mechanisms, mechanical structure, control, optimized odometry system, omni-vision sensor for self localization and other subjects related to soccer player robot’s software.
Topological Navigation of Simulated Robots using Occupancy Grid, Page 201-206 Abstract: Formerly I presented a metric navigation method in the Webots mobile robot simulator. The navigating Khepera-like robot builds an occupancy grid of the environment and explores the square-shaped room around with a value iteration algorithm. Now I created a topological navigation procedure based on the occupancy grid process. The extension by a skeletonization algorithm results a graph of important places and the connecting routes among them. I also show the significant time profit gained during the process.
Design and Implementation of a General Decision-making Model in RoboCup Simulation, Page 207-212 Abstract: The study of the collaboration, coordination and negotiation among different agents in a multi-agent system (MAS) has always been the most challenging yet popular in the research of distributed artificial intelligence. In this paper, we will suggest for RoboCup simulation, a typical MAS, a general decision-making model, rather than define a different algorithm for each tactic (e.g. ball handling, pass, shoot and interception, etc.) in soccer games as most RoboCup simulation teams did. The general decision-making model is based on two critical factors in soccer games: the vertical distance to the goal line and the visual angle for the goalpost. We have used these two parameters to formalize the defensive and offensive decisions in RoboCup simulation and the results mentioned above had been applied in NOVAURO®, original name is UJDB, a RoboCup simulation team of Jiangsu University, whose decision-making model, compared with that of Tsinghua University, the world champion team in 2001, is a universal model and easier to be implemented.
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ARS Web 2004 |