|
4. Dynamic evolution model of the cooperation between robot teams
The dynamic evolution of the cooperative relationship between robot teams is an adaptive means to solve questions of environment and demands of tasks. According to the adaptation to the solving environment, there are two ways to form the team. One is to design the team structure in advance, based on the question solving demands and various constrains. The team structure does not change in the whole problem solving process. And to solve interaction between robots, the task segregation problem and the load balance problems is relatively simple because of the static robot team structure. The shortcoming is that it can not solve problems well in the open environment or when goals are changing during the problem solving process. And the problem solving ability will decrease or even inaccessible when environment is changing. Another way to organize the robot team is to change the team structure after it has formed by environment and the demands of the problem to be solved. It is called the dynamic evolution of the team cooperative relationship. Because the team cooperation system is an open system, environment restrictions and the goal of problem solving will change continuously. So the team cooperative relationship with dynamic evolution ability should adapt to environment better, with better problem solving efficiency and lower computational complexity. Dynamic evolution of the cooperative relationship between robot teams can be recognized by the following characters: temporary cooperation between teams with same goals, in order to complete complex tasks and share risks and interests. Each robot team focus on the core ability of the team itself and take on the strategies to cooperate with outside teams. The dynamic evolution realization of the cooperative relationship between the robot teams does not mean to organize one more layer beyond the team structure, but to decrease the cost of forming a team by deepen inner cooperation and the interacting system between teams. Dynamic evolution of the cooperative relationship between robot teams is formed by more than two teams cooperating in a limit period of time to benefit each other, get maximum benefits and sense the unknown environment most quickly with the minimum costs. It optimizes the team and dies with the finishing of the common goal. Fig.2 gives a dynamic evolution model of the cooperative relationship between teams, in which the cooperative relationship between teams plays an important role. This model consists of three layers: cooperative entity layer, ability layer and the relational layer. Robots in the cooperative entity layer have the ability to finish assigned tasks in a given time with limited recourses and maximize its benefits. Robots in the ability layer treat “objects” with strong operability as core. In fact, the computation from the Ce layer to Ab layer is an objectoriented design process. Team is the basic unit of relational layer and it can make each team exert its own advantages to finish the common task quickly and efficiently between different teams. Integration, optimization and cooperation are cores of this layer. The dynamic evolution of this cooperative relationship model between teams is finished in the relational layer. Major factors that can effect the cooperative relationship formation between teams are the types of the cooperative entities under new environment demands, which are called payoff function. Suppose the actions behaved in the environment tasks of the robot team are connect to each other, then how to define the best action set based on the payoff function when cooperative entities confronting new environment demands becomes a necessary decision-making problem that must be solved during the dynamic evolution process of the cooperation between robot teams. The basis of the decision-making can be divided into two kinds-to maximize payoff function of the whole robot team and to maximize payoff function of members in robot team. Suppose new-formed robot team is formed by n cooperative entities, and each entity can build a cooperative relationship with other n-1 entities. We set aij as the action relating with the formation of cooperative relationship during the interaction of robot CRi and CR j under new demands of tasks.
Here the evolving question of the team formation is converted to the combination optimization question to seek the action set A*i when Ci is maximized. The search space of the optimization question is a discrete finite mathematical structure that can be represented by binary coding, to use evolutionary computation to analysis the evolving process of the team cooperation. 5. Conclusion
A good robot organization model should be able to improve the efficiency of the system, reduce the complexity of robot interactions, and detract the difficulty of computation. From the sociology aspect of topology, structure and organization, this paper first studies the multi-robot organization formation. It presents and describes in detail a Hierarchical-web Recursive Organization Model. It defines individual robots and team leaders in different levels as the same structure by the united framework and describes the organization model by the recursive structure, so it is helpful to represent the formation of various organizations in the dynamic surroundings. Second this paper aims at the situation that most of the research on the cooperation between robot teams is still on the stage of quantitatively analysis, with few works on descriptions and forecasts on the dynamic evolution process of cooperation with the changing demands of tasks. We proposed a cooperative mechanism from the cooperative entity layer and ability layer to the relational layer of the robot teams, using Markov process and the evolutionary computation. We also described a dynamic evolving model of the cooperative relationship between robot teams, which is novel now. This model can not only describe the cooperative relationship status between robot teams, but also using finite Markov chain and evolutionary computation to describe whether the dynamic evolution process really forms in the cooperation qualitatively. With this model, users can both handle the cooperative situation globally and dynamically and predict the new cooperative relationship and the actions of robot teams when they confronting new demands of tasks. Page 1, 2 , 3 , 4
Tech Materials (Free)
Robot Team Cooperation A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation
Kuka Robots For ONU ONU Robotics Technology Center of Excellence, powered by KUKA Robotics Corporation
Augmented reality Annotation System for Robotic Application
Modular Robots Self-Reconfiguration Planning Of Identical Modules
Autonomous robots A New Approach To Robotics
Robotic Mounting Flat Panel Displays With Robotic Mounting
Calibration of Industrial Robots A Photogrammetric Robot Calibration System Based On Off-The-Shelf Low Cost Hardware Components
Vision System For Robots Adding Vision Guidance To A Robot
Robot Assistive Tasks User-Guided Reinforcement Learning for an Intelligent Environment
Wireless Systems Learn The Science And Engineering Of Mobile And Wireless Communicaitons
More... Amazon Books
|
