Fig 3 - uploaded by Milan Rollo
Content may be subject to copyright.
Source publication
Within this paper we describe a simulation environment for the underwater surveillance and propose architecture of control
part of autonomous robot capable of efficient operation in such environment. Besides this the algorithms for decentralized
coordination within a group of such robots and video stream transmission path planning are discussed. De...
Similar publications
Abstract This thesis investigates the use of Genetic Programming,(GP) to evolve controllers for an autonomous,robot. GP is a type of Genetic Algorithm (GA) using the Darwinian idea of natural selec- tion and genetic recombination, where the individuals most often is represented as a tree-structure. The GP is used to evolve a population of possible...
An autonomous robot involved in long and complex missions should be able to generate, update and process its own plans of action. In this perspective, it is not plausible that the meaning of the representations used by the robot is given from outside the system itself. Rather, the meaning of internal symbols must be firmly anchored to the world thr...
La robótica es una industria en constante crecimiento debido a que los seres humanos buscan delegar en robots tareas rutinarias y costosas, tareas que son difíciles o peligrosas de ejecutar. Las investigaciones actuales están orientadas a incorporarles inteligencia, autonomía y distintas capacidades para adaptarse a estos desafíos. En este trabajo...
Successfully accomplishing everyday manipulation tasks re-quires robots to have substantial knowledge about the objects they interact with, the environment they operate in as well as about the properties and effects of the actions they per-form. Often, this knowledge is implicitly contained in man-ually written control programs, which makes it hard...
![Figure 2. Arduino Uno Board [10].](profile/Shadman-Ahmad/publication/315624159/figure/fig1/AS:475731512827904@1490434639534/Arduino-Uno-Board-10_Q320.jpg)
![Figure 3. Ultrasonic Sensor HC-SR04 [9].](profile/Shadman-Ahmad/publication/315624159/figure/fig2/AS:475731512827905@1490434639551/Ultrasonic-Sensor-HC-SR04-9_Q320.jpg)
![Figure 4. SG90 Tower Pro Servo Motor [13].](profile/Shadman-Ahmad/publication/315624159/figure/fig3/AS:475731512827906@1490434639629/SG90-Tower-Pro-Servo-Motor-13_Q320.jpg)
![Figure 5. Bluetooth Module HC-05 [14].](profile/Shadman-Ahmad/publication/315624159/figure/fig4/AS:475731512827907@1490434639670/Bluetooth-Module-HC-05-14_Q320.jpg)
This article provides a basic level introduction to 3D mapping using sonar sensors and localization. It describes the methods used to construct a low-cost autonomous robot along with the hardware and software used as well as an insight to the background of autonomous robotic 3D mapping and localization. We have also given an overview to what the fu...
Citations
... Institute for Human and Machine Cognition (IHMC) in collaboration with the Gerstner Laboratory, CTU developed an agent-based simulation of robotics Coordination, negotiation, simulation , adjustable autonomy Simulation, control, planning Agent-based software prototypes, deployed products sweeping exercise of collective underwater robots. The multi-agent coordination technology has been successfully migrated from simulation to the robotic environment [67]. Rockwell Automation also used the presented technology for simulating drinking water and waste water distribution in a municipal distribution network. ...
This paper reports on industrial deployment of multi-agent systems and agent technology. It provides an overview of several
application domains and an in-depth presentation of four specific case studies. The presented applications and deployment
domains have been analyzed. The analysis indicates that despite strong industrial involvement in this field, the full potential
of the agent technology has not been fully utilized yet and that not all of the developed agent concepts and agent techniques
have been completely exploited in industrial practice. In the paper, the key obstacles for wider deployments are listed and
potential future challenges are discussed.
... Over the past few years there has been a significant increase in the development and deployment of physical systems that are controlled by intelligent software agents [18] because agent technology is well suited to domains where openness, responsiveness to change and decentralised control are paramount. Examples of agent-based control systems can be found in domains like: holonic manufacturing for various applications such as mass-customisation [13], robotics [7] and production planning [10]; logistics where they are integrated with RFID technology to provide sophisticated tracking and identification of goods [6] [3]; and defence for controlling uninhabited air, ground and underwater vehicles [17] [12]. ...
Today there is a proliferation of research into systems based on the autonomous agent, multi-agent and holonic paradigms. These systems are being applied to environments including manufacturing, logistics, defense, and supply chain management to increase the flexibility, realism, openness and mass-customization of real-world decentralized operations. It is now well recognized that prior to deploying agents into any physical environment where machines or any form of hardware is controlled by the agents, a key step in verifying the functionality and reliability of the agent-based control system must take place, namely simulation of the agents' actions and their interactions. However, there is very little formal basis or methodological practice for creating a robust simulation of the distributed agent-based control system that would be used in a physical setting. This paper takes an initial step in trying to identify a set of design questions that must be answered by the agent system developer as part of the instantiation of the agents in the simulation
In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is rational). Intelligent agents may also learn or use knowledge to achieve their goals. Intelligent agents in artificial intelligence are closely related to agents in economics, and versions of the intelligent agent paradigm are studied in cognitive science, ethics, the philosophy of practical reason, as well as in many interdisciplinary socio-cognitive modeling and computer social simulations. A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to software agents. However, the agents in a multi-agent system could equally well be robots, humans or human teams. A multi-agent system may contain combined human-agent teams. This work introduces a brief distribution about Intelligent Agent and Multi Agent Systems.
This paper describes a design, development and experience with an universal multi-robotic robot control system. The overall message-driven system concept is introduced together with its open modular architecture. Besides the description of functionalities of basic modules, the approach to the system configuration and hardware abstraction layer is discussed. The control system allows to manage different types of robots in one team, whereas each team member is able to share and interchange any information with other team members. Since a lot of robotic tasks are computationally intensive and cannot be computed onboard, the system allows to distribute selected subtasks among remote computers. The system has been designed as a test-bed for research of new algorithms from an area of cooperative robotics.
A-globe (Speretta and Gauch, 2005) is a simulation oriented multi-agent platform featuring agent migration, communication inaccessibility simulation and high scalability with moderate hardware requirements. Using dedicated simulation messaging together with 2D and 3D visualization support, large agent systems can be engineered, tested and visualized on a single machine. A-globe agents are fully fledged JAVA agents, each with its own independent thread that can autonomously migrate between platforms running on different hosts. Thanks to the separation of simulation and agent code, deployment of agents to embedded devices is straightforward. Platform is not natively FIPA-compliant, as the interoperability was sacrificed to support the scalability and efficiency.
Mobile ad-hoc networks (MANET) are expected to form the basis of future mission critical applications such as combat and rescue operations. In this context, communication and computational tasks required by overlying applications will rely on the combined capabilities and resources provided by the underlying network nodes. This paper introduces an integrated FlexFeed/A-globe technology and distributed algorithm for opportunistic resource allocation in resource- and policy-constrained mobile ad-hoc networks. The algorithm is based on agent negotiation for the bidding, contract and reservation of resources, relying primarily on the concept of remote presence. In the proposed algorithm, stand- in Agents technology is used to create a virtual, distributed coordination component for opportunistic resource allocation in mobile ad-hoc networks.
