Group-living animals often exhibit complex collective behaviors that emerge through the non-linear dynamics of social interactions between individuals. Previous studies have shown that it is possible to influence the collective decision-making process of groups of insects by integrating them with autonomous multi-robot systems. However, generating robot controller models for this particular tas...

We propose a novel method to solve a kidnapped robot problem. A mobile robot plans its sensor actions to localize itself using Bayesian network inference. The system differs from traditional methods such as simple Bayesian decision or top-down action selection based on a decision tree. In contrast, we represent the contextual relation between the local sensing results and beliefs about the glob...

We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selection. The MRF model is well-suited to domains in which the joint probability over latent (action) and observed (perceived) variables can be factored into pairwise interactions between these variables. Specifically, these ...

joint flexibility is a very important factor to consider in the controller design for robot manipulators if high performance is expected. most of the research works on control of flexible-joint robots in literature have ignored the actuator dynamics to avoid complexity in controller design. the problem of designing nonlinear controller for a class of single-link flexible-joint robot manipulator...

In human-robot interaction, it is important for the robots to adapt to our ways of communication. As humans, rules of non-verbal communication, including greetings, change depending on our culture. Social robots should adapt to these specific differences in order to communicate effectively, as a correct way of approaching often results into better acceptance of the robot. In this study, a novel...

Selecting an optimal position for each soccer robot to move to in a robot football game is a challenging and complex task since the environment and robot motion are so dynamic and unpredictable. This paper provides an overview of behaviour-based position selection schemes used by Essex Wizards’99 simulated soccer team, a third place in RoboCup’99 simulator league at Stockholm. The focus concent...

This paper presents a novel action selection method for multi robot task sharing problem. Two autonomous mobile robots try to cooperate for push a box to a goal position. Both robots equipped with object and goal sensing, but do not have explicit communication ability. We explore the use of fuzzy signatures and decision making system to intention guessing and efficient action selection. Virtual...

In this paper we address the problem of learning behaviors for autonomous mobile robots. We particularly focus on methods which enable a human user to train a robot in its real destination environment without giving an a-priori model. Using complex visual input typical of real situations in office environments we show that very simple visual features can be used to represent the perception/acti...

With the continuous development of the industrialization process, the countries all over the world gradually appeared lack of agricultural labor force and aging phenomenon, which was especially prominent in developed countries. However the agricultural robot with high operating efficiency, high qualities of work will play an increasingly important role in future agricultural production. Robot n...

In multi-robot simultaneous localization and mapping (SLAM) systems, the system must create a consistent global map with multiple local maps loop closures between robot poses. However, false-positive caused by perceptual aliasing can severely distort map, especially in GNSS-denied areas, where good prior of relative poses robots is unavailable. addition, performance consistency metric existing ...