The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 89-433
Full Name: Gabriela Tont
Position: Professor
Age: ON
Sex: Female
Address: University of Oradea, Department of Electrical Engineering, Measurements and Electric Power Use
Country: ROMANIA
Tel:
Tel prefix:
Fax:
E-mail address: gtont@uoradea.ro
Other E-mails: luigiv@arexim.ro
Title of the Paper: Markov approach of Adaptive Task Assignment for Robotic System in Non-Stationary Environments
Authors as they appear in the Paper:
Email addresses of all the authors:
Number of paper pages: 10
Abstract: Abstract: - Adaptive and decentralized task assignment in non-uniform and possibly even non-stationary conditions with the aim of ensuring stability is especially challenging knowledge requirements in order to negotiate within and interact with uncertain and dynamic environments such as robot malfunctions or error propagation. Task assignment addresses to the problem of coordination both in on autonomous and interacting robot. In the scenarios for task assignment robots are embedded in the environment, there are strict constraints on communication, and most importantly tasks that robots should execute are perceived by the robot itself during the mission execution, thus conflicts on the task assignment process might arise. The internal representation of timing constraints on interaction has many implications for the reliability, effectiveness, efficiency, validity, schedulability and robustness of the mobile robot. The task assignment processes and its control imply!
ing reasoning about objects and resources and their changing states are dominated by either discrete or stochastic-event dynamics or both. Stationarity is an unrealistic prior assumption for the multi-state components of complex systems. The numerical characteristics of the nonstationary random responses of complex structure are developed in the paper considering the uncertainty and volatility of process transitions states. The appropriate functional levels of multi-state systems components are placed between the two extremes: defect (0%) and the nominal (100%) state, allowing any intermediate state transiting from the range of perfect functionality to complete failure. Time analysis interval of a multi-state system is characterized by intermediate states (states of partial success). The paper proposes a stochastic model of assessing system probability of unidirectional or bidirectional transition states, applying the non-homogeneous (non-stationary) Markov chain. The capab!
ility of timedependent method to describe a multi-state system is base
d on a case study, assessing the operatial situation of robotic system. The rationality and validity of the presented model are demonstrated via an example of quantitative assessment of states probabilities of an autonomous robot.
Keywords: Key-Words: -.Petri nets, Fuzzy sets, mobile robots, non-stationary discrete event, dynamic systems, reasoning
EXTENSION of the file: .pdf
Special (Invited) Session: Fuzzy Petri Net -Based Approach in Modelling Simultaneous Task Assignment for Robotic System
Organizer of the Session: ID629-338
How Did you learn about congress:
IP ADDRESS: 93.122.207.231
