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This paper presents a new path planning approach, in which the MAKLINK graph is constructed to describe the complex environment of the mobile robot, the enumeration method ideas into Dijkstra algorithm is used to obtain the shortest path, and the dynamic double mutation particle swarm optimization algorithm is adopted to get the optimal path. Finally, simulation results are used to illustrate the...
Garbage recycling and collection problem is an interesting problem that researchers are applying swarm intelligence algorithms to solve. Some previous approaches used particle swarm optimization, immune systems and ant colony optimization algorithms and achieved good results. Ant colony optimization is a well-known swarm intelligence algorithm that is normally used to solve computational problems...
This paper researches the alliance generation algorithm with emotional factors on the basis of multiple robots pursuit-evader problem. Firstly, this paper constructs an emotional model for pursuit robots: we not only apply the basic emotion method to the emotional expression, but also simulate the process of emotional transfer with Hidden Markov Model (HMM). Secondly, we determine the cooperation...
Odor source localization is very important in real-world applications. We studied the problem of odor source localization and presented a modified particle swarm optimization algorithm for odor source localization of multi-robot. The algorithm dynamically adjusts two learning factors in the velocity update equation based on the effect of wind on self-cognition and social cognition of a particle. In...
Man has always tried to make new systems, which can do his difficult tasks. Manage and control of such new complex systems is new challenge in our life. Today, one solution to deal with this challenge is using advantage of features of autonomy. It means that instead of managing and controlling the entire system, each component or at least part of the system can manage or control itself even in unpredictable...
Robot path planning is an important research topic in robotics field. The paper proposes an algorithm based on the combination of Ant Colony Optimization(ACO) and Particle Swarm Optimization(PSO) for path planning. The new algorithm combines the advantages of ACO and PSO effectively and generates the distribution of the initial information for ACO by using the merits of high efficiency and concision...
The cooperation of robotic systems over wireless network results in some challenges, finite network bandwidth, and limited node energy. A novel co-design approach is presented by means of combining deadband-control with dynamic prediction in this paper. To reduce the network traffic and energy consumption, the control packets of "Controlling" robots are only sent if the response error and...
A collective construction task require a multi-robot system to search for randomly distributed building blocks and push those blocks to some predefined locations. To address this problem, a bio-inspired swarm intelligence based algorithm is proposed for a distributed multi-robot system to combine explorative searching and dynamic task allocation together for collective construction. Basically, a virtual...
In this article we discuss a decentralized totally asynchronous realization of the particle swarm optimization (PSO) algorithm, which is suitable for parallel implementation. The proposed method has important differences from the PSO implementations considered in the literature. In the proposed method the particles are allowed to exchange information and to update their estimates at totally independent...
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