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“Gain-Based Separation” is a novel heuristic that modifies the standard multiclass decision tree learning algorithm to produce forests that can describe an example or object with multiple classifications. When the information gain at a node would be higher if all examples of a particular classification were removed, those examples are reserved for another tree. In this way, the algorithm performs...
Inspired by the simplicity of how nature solves its problems, we implement a bacteria controller on a physical platform that would enable the localisation and subsequent mapping of environmental pollution. We investigate the effects of each parameter in the controller on the localisation and exploration ability of the platform used. We also present how we can tune the controller for a given environmental...
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...
This paper presents an optimal method based on combination of artificial potential field (APF) and ant colony optimization (ACO) algorithms for global path planning of mobile robots working in partially known environments. Two steps constitute this approach. Firstly, free space model of mobile robot is established by using visible graph method and ACO algorithm is utilized in this model to search...
Nowadays, mobile robots work under the dynamic environments like manufacturing industries with machinery parts as moving objects and are using many techniques for navigation, obstacle avoidance, and localization. In this work we are using pioneer 2 DX mobile robot for experiments. This paper focuses on development of algorithms with the integration of path planning by potential field method and Monte...
We propose an algorithm for adaptive formation transitions of a robot group composing autonomous, nonlabeled robots. In the proposed system, one leader robot that knows the target position guides the other robots; the other robots do not have any global information. Each individual robot is equipped with a nonlinear oscillator and a simple communication system realized by LED flashlights and photodetectors...
The thesis presented a heterogeneous players strategy using in RoboCup. The strategy used fuzzy evaluation to obtain the evaluation results of all heterogeneous players on various roles, and constructed a fuzzy inference system to dynamically select equal heterogeneous players for various roles. The simulation experiments and competition results show the application is feasible and effective.
This paper presents a new real-time path planning algorithm in dynamic uncertainty environment, and it has well real-time and high applicability. This algorithm is composed by two parts. The first part is the analysis and interpretation of the environment information by searching the characteristic information (double safe edges DSE), so the algorithm can catch the dynamic obstacle and estimate the...
Many collision detection methods exist, each specialized for certain data types under certain constraints. In order to enable rapid development of efficient collision detection procedures, we propose an extensible software architecture that allows for cross-queries between data types, while permitting the time and memory optimizations needed for high-performance. By decomposing collision detection...
This paper proposes a simulated annealing based approach to determine the optimal or near-optimal path quickly for a mobile robot in dynamic environments with static and dynamic obstacles. The approach uses vertices of the obstacles to define the search space. It processes off-line computation based on known static obstacles, and re-computes the route online if a moving obstacle is detected. The contributions...
This paper mainly uses flocking control algorithm to implement the ldquobiodsrdquo model of Reynolds among multi-robots. We present two flocking algorithms: the first algorithm is a gradient-based algorithm with a velocity consensus protocol, and the second one is the main flocking algorithm for robot formatin control in a free workspace with an additional target steering agent that takes the group...
This paper addresses the problem of estimating the odor path which is most likely taken by the odor patch detected by the concentration sensor on a mobile robot moving in an indoor dynamic airflow environment. The odor path estimation is useful for plume tracing and odor source declaration. A novel algorithm for odor path likelihood mapping in the dynamic airflow environment is proposed. The algorithm...
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...
In this paper, a fuzzy-inference controller with Accelerate/Brake (A/B) Module is proposed for navigation control of a mobile robot in dynamic environments. This approach includes target seeking, obstacle avoidance, and optimal path planning. By utilizing the fuzzy controller, a mobile robot could approach a target in a dynamic environment autonomously. The A/B Module of the proposed system is to...
We present robust localization algorithm using particle filter for mobile robots. The blueprint of building that cannot completely represent the real environment or a simple map of environment can be used in this work. With this incomplete information, it will not be easy to estimate the pose of robots because un-modeled obstacles will make the sensor observation inconsistent. Proposed algorithm provides...
Reinforcement learning has been commonly used in multi-robot decision making to cope with uncertainties in the environment. A shortcoming of this approach is the need for the robots to change their actions quite frequently, which is not feasible in a physical multi-robot system. This paper focuses on the development of a modified Q-learning algorithm with minimal switching of actions. By introducing...
The Rapidly Exploring Random Tree (RRT) algorithm can be applied to the robotic path planning problem and performs well in challenging, dynamic domains. Traditional RRT methods use a binary cost function and they select portions of the tree for expansion based on the Euclidean distance to the target. However, in outdoor navigation, the relative cost of terrain can also provide useful input to a planning...
Hybrid sensor networks (HSNs), made up of many static sensors interacting with a limited number of mobile robotic sensors, can support a variety of applications in which assisted navigation, implemented for mobile robotic sensors, performs requested operations in hostile environments, where the human presence is impracticable. On the other hand, the limited on-board battery energy of the sensor nodes...
This paper proposes an efficient dynamic localization algorithm in the active beacon sensor space for the precise localization of a mobile robot. The design and implementation of the localization system is based on the use of active beacon systems, each of which is composed of an RFID receiver and an ultrasonic transmitter. The RFID receiver obtains the synchronization signal from the mobile robot...
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