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Hypothesis Testing for Complex Agents
Hypothesis Testing for Complex Agents

... added by difference in interpretation of a category can lose correlations between subjects that actually agree on the relative validity or likeability of two systems. Further, we would really prefer in many circumstances to have a continuous range of difference values. Such results can be provided b ...
TOWARDS THE DREAM OF AN INTELLIGENT, VISUALLY
TOWARDS THE DREAM OF AN INTELLIGENT, VISUALLY

... while providing the same personal freedom. This idea continues to motivate the project today. PlayBot’s goals include: i) to use vision as the key sensing modality, as humans do; ii) for perceptual processing be task-directed, as it has been long established that task direction is a key strategy in ...
A Taxonomy of Artificial Intelligence Approaches for Adaptive
A Taxonomy of Artificial Intelligence Approaches for Adaptive

... of as a surrogate for human experts. This approach is motivated by the lack of expert availability and coordination concerns (e.g., logistics of gathering all relevant experts in one place at one time). Experts are solicited for general rules that they use to make decisions within a particular domai ...
artificial intelligence research in particle accelerator control
artificial intelligence research in particle accelerator control

... reasoning system searches the oriented graph defined by an object description to make decisions about equipment setup without human assistance. The program provides a good example of using object models for control decision making. It does not attempt to perform real-time control or use on-line feed ...
sv-lncs - HEIG-VD
sv-lncs - HEIG-VD

... computers (and microprocessors), even if sometimes, conceptually, other implementation media are discussed (e.g., simulation of neurons, generations of evolving populations, virtual ants, etc.). Progress in microelectronics, software technologies, communication and network engineering is such that t ...
Definition of a `Robot`
Definition of a `Robot`

... the quality of life by freeing workers from dirty, boring, dangerous and heavy labor. it is true that robots can cause unemployment by replacing human workers but robots also create jobs: robot technicians, salesmen, engineers, programmers and supervisors. The benefits of robots to industry include ...
Towards a theory of Hybrid Intelligent Autonomous Systems
Towards a theory of Hybrid Intelligent Autonomous Systems

... been actively studied and applied to domains such as automatically control of complex systems like robot. In fact, recognition, learning, decision-making, and action constitute the principal obstacle avoidance ...
A Novel Method for Developing Robotics via Artificial Intelligence
A Novel Method for Developing Robotics via Artificial Intelligence

... 4.4 Internet of Things The next wave in the era of computing field will be outside the realm of the traditional desktop. At present, the definitions of "Internet of Things" are manifold; they vary depending on the context, the effects and the views of the person giving the definition. But we can say ...
Types of Robots
Types of Robots

... Most of the future developments in the robotics industry might continue to be the product of research at universities' laboratories. As time goes on and the existing technology is improved, customers will demand robots that can perform their tasks at higher speeds while still making consistently hig ...
Introduction to Swarm Robotics
Introduction to Swarm Robotics

... assembly robots”. Basically, these robots consists of modules, which, in response to environment, stimuli, or simulated pheromones [9], may reconfigure itself for some reason - such as getting around an obstacle. Richard Beck[3] explained the typical physical requirements for these robots: ...
Soar - Information Sciences Institute
Soar - Information Sciences Institute

... – Select: create preferences to propose and compare operators – Apply: modify the current situation, send motor commands – Terminate: determine that operator is finished Elaboration (apply operator) ...
What are Agent and Environment?
What are Agent and Environment?

... The most famous artificial environment is the Turing Test environment, in which one real and other artificial agents are tested on equal ground. This is a very challenging environment as it is highly difficult for a software agent to perform as well as a human. ...
Unit1_1 - คณะเทคโนโลยีสารสนเทศและการสื่อสาร มหาวิทยาลัยพะเยา
Unit1_1 - คณะเทคโนโลยีสารสนเทศและการสื่อสาร มหาวิทยาลัยพะเยา

... environment via sensors and acts rationally upon that environment with its actuators. Hence, an agent gets percepts one at a time, and maps this percept sequence to actions. ...
Artificial Intelligence and Mobile Robots: Successes
Artificial Intelligence and Mobile Robots: Successes

... heterogeneous robots •“On-the-fly” teaming of robots •Distributed sensing •Tasks that require multiple robots ...
Robotics and Autonomous Systems in the 50th Anniversary of
Robotics and Autonomous Systems in the 50th Anniversary of

... The special issue on “Robotics and Autonomous Systems in the 50th Anniversary of Artificial Intelligence” collects a subset of the best papers in the fields of Robotics and Autonomous Systems presented at the Campus Multidisciplinary in Perception and Intelligence, CMPI-2006 [1]. The CMPI-2006 inter ...
MIT mobile robots-what`s next? - Cooperative Robotics Research
MIT mobile robots-what`s next? - Cooperative Robotics Research

... the art in terms of the level of intelligence attainable is not very high. Second, a considerable portion of the sheer bulk on most mobile robots has nothing a t all to do with the intelligence system. There seems t o be a certain runaway characteristic involved with the sizes of motors and batterie ...
30200385.pdf
30200385.pdf

... dynamic environments against unknown, competing agents. These conditions require an integrated, systematic approach that simultaneously addresses the problems of effective cooperation between robots while allowing fast, smooth reaction to ever changing conditions. This paper addresses such multi-rob ...
Reexamining Behavior-Based Artificial Intelligence
Reexamining Behavior-Based Artificial Intelligence

... representation” as a mantra, most attributed the impressive success of Brooks approach to the fact that he had created abstracted primitives — the action/perception modules. Because these primitive units could sort out many of the details of a problem themselves, they made the composition of intelli ...
Building a multimodal human-robot interface
Building a multimodal human-robot interface

... When the robotic system receives this translation, it notes what action it must take (and checks if a gesture is needed). If the information is complete, the robotic system translates this expression into a command that produces an action, which causes a robot to move. Context predicates also hold i ...
The First Law of Psychology is the Second Law of Thermodynamics
The First Law of Psychology is the Second Law of Thermodynamics

... Ongoing energy management – its acquisition, storage, allocation, distribution and utilization for all life processes—was the most critical adaptive problem that ancestral life forms had to solve, and this priority is reflected in the evolved design of both plant and animal intelligence systems (La ...
Title Social robotics - Research Repository UCD
Title Social robotics - Research Repository UCD

... correspondence between systems of multiple agents and systems of multiple robots. Research in the multi-agent community has concentrated primarily on software agents with little or no physical manifestation of their behaviour. Research in the robot community has focused on non-collaborative robotic ...
robotics - Suraj @ LUMS
robotics - Suraj @ LUMS

... materials. Robots such as HAZBOT also hold potential for use in mining and law enforcement. "It's almost standard now to have robots on bomb squads in major cities, but it took several years for the idea to catch on," said Richard Welch, task manager of Emergency Response Robotics at JPL. ...
Dance Choreography Design of Humanoid Robots using Interactive
Dance Choreography Design of Humanoid Robots using Interactive

... various sounds and also to generate sounds from motions using the back-propagation through-time algorithm. Other approach from Tokyo University is using Chaos to trade synchronization and autonomy in a dancing robot. Dancing Robot Partner built at the Tohoku University is well-known in the domain of ...
to get the file - Mechanical and Materials Engineering
to get the file - Mechanical and Materials Engineering

... During the past twenty years the use of industrial robots that are equipped not only with precise motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. Intelligent robot products h ...
Why Robot Nannies Probably Won`t Do Much Psychological Damage
Why Robot Nannies Probably Won`t Do Much Psychological Damage

... What may change is how much attention that person can devote to other things, or ...
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Adaptive collaborative control

Adaptive collaborative control is the decision-making approach used in hybrid models consisting of finite-state machines with functional models as subcomponents to simulate behavior of systems formed through the partnerships of multiple agents for the execution of tasks and the development of work products. The term “collaborative control” originated from work developed in the late 90’s and early 2000 by Fong, Thorpe, and Baur (1999). It is important to note that according to Fong et al. in order for robots to function in collaborative control, they must be self-reliant, aware, and adaptive. In literature, the adjective “adaptive” is not always shown but is noted in the official sense as it is an important element of collaborative control. The adaptation of traditional applications of control theory in teleoperations sought initially to reduce the sovereignty of “humans as controllers/robots as tools” and had humans and robots working as peers, collaborating to perform tasks and to achieve common goals. Early implementations of adaptive collaborative control centered on vehicle teleoperation. Recent uses of adaptive collaborative control cover training, analysis, and engineering applications in teleoperations between humans and multiple robots, multiple robots collaborating among themselves, unmanned vehicle control, and fault tolerant controller design.Like traditional control methodologies, adaptive collaborative control takes inputs into the system and regulates the output based on a predefined set of rules. The difference is that those rules or constraints only apply to the higher-level strategy (goals and tasks) set by humans. Lower tactical level decisions are more adaptive, flexible, and accommodating to varying levels of autonomy, interaction and agent (human and/or robotic) capabilities. Models under this methodology may query sources in the event there is some uncertainty in a task that affects the overarching strategy. That interaction will produce an alternative course of action if it provides more certainty in support of the overarching strategy. If not or there is no response, the model will continue performing as originally anticipated.Several important considerations are necessary for the implementation of adaptive collaborative control for simulation. As discussed earlier, data is provided from multiple collaborators to perform necessary tasks. This basic function requires data fusion on behalf of the model and potentially a need to set a prioritization scheme for handling continuous streaming of recommendations. The degree of autonomy of the robot in the case of human-robot interaction and weighting of decisional authority in robot-robot interaction are important for the control architecture. The design of interfaces is an important human system integration consideration that must be addressed. Due to the inherent varied interpretational scheme in humans, it becomes an important design factor to ensure the robot(s) are correctly conveying its message when interacting with humans.
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