Showing papers by "Eugenia Minca published in 2011"

Trajectory-tracking and discrete-time sliding-mode control of wheeled mobile robots

Abstract: In this paper a discrete-time sliding mode control for the trajectory tracking problem of wheeled mobile robots is presented. The wheeled mobile robot (WMR) taken into account was PowerBot. PowerBot is a mobile platform with two differential driving wheels (2DW) and two balancing caster wheels. It is an automated guided vehicle specially designed and equipped for autonomous, intelligent delivery and handling of large payloads. PowerBot is a member of MobileRobots' Pioneer family of mobile robots, which are research and development platforms that share a common architecture, foundation software and employ intelligence-based client-server robotics controls. Due to its size and high load carrying capacity PowerBot is an ideal robot for both, indoor and outdoor transportation. The algorithm has been designed in discrete-time domain in order to avoid problems caused by the discretization of continuous-time controllers. The simulation results and real time results prove the effectiveness of the proposed controller.

Adaptive disassembly sequence control by using mobile robots and system information

Abstract: Assembly and disassembly processes are similar from the viewpoint of automation. Assembly process is more or less a “classical” subject; disassembly process is more a quite new field. Flexible system are very important issue in the current industry when disassembling and recycling tasks have to be performed. These tasks can be performed by a human operator or by a robot system. In this paper an autonomous robot with manipulator system perform the required task for different operation. This system takes into consideration the necessary task to perform the disassembly of a component using robots synchronization with flexible line process. The proposed algorithm is to distribute the task among the robot and flexible line and takes into consideration the characteristics of each sequence that needs to be followed to perform the required disassembly of the product. The proposed system is validated by experiments using several types of components.

Discrete-time sliding mode control of wheeled mobile robots

Abstract: In this paper a discrete-time sliding mode control for the trajectory tracking problem of wheeled mobile robots is presented. The wheeled mobile robot taken into account was Powerbot. PowerBot is a mobile platform with two differential driving wheels (2DW) and two balancing caster wheels. It is an automated guided vehicle specially designed and equipped for autonomous, intelligent delivery and handling of large payloads. PowerBot is a member of MobileRobots' Pioneer family of mobile robots, which are research and development platforms that share a common architecture, foundation software and employ intelligence-based client-server robotics controls. The algorithm has been designed in discrete-time domain in order to avoid problems caused by the discretization of continuous-time controllers. The simulation results and real time results prove the effectiveness of the proposed controller.

Assembly-disassembly flexible lines and collaborative robots considered as hierarchical systems in temporal recurrent modelling

Abstract: This article proposes a temporal recurrent approch of hierarchical systems modeling, symplifing prevoius tools in thies area of th authors. The states of the systems are supposed known for system functioning at every occurence moment. In addition to them, appear external events for nonautonomus system sysncronisation {s i }, with transitions in Temporised Recurrent Petri Nets (TRecPN) model. The sysncronised signals are defined on an assembly of subsets, conditioned by the moment of occurence and the temporal interval when are expected in network. This approch permits an hierarchical approch on levels of Petri Net model. The refining process of the model is made on horisontal. In each place is a PN model, each one is linked with a distinct temporal interval represented by a syncronised signals subset. In an explected syncronised signal doesn't appears, the model functioning will be stoped. Each level is linked with a LIFO object placed on a lower level dedicated to the transfer of the last state reache by the system. In this context, two type of applications are proposed: a) recurrent detection function modelling; b) manufacturing system served by colaborative robots support.

MLP neural network as load forecasting tool on short- term horizon

Abstract: This paper focus on multilayer feedforward neural networks, the most popular and widely-used paradigms in many applications, including energy forecasting Precisely, it provides a multilayer perceptron (MLP) architecture, capable to forecast the DPcg (difference between the electricity produced and consumed) in relation with solar radiation, for short- term horizon. The forecasting accuracy and precision, in capturing nonlinear interdependencies between the load and solar radiation of this structure is illustrated and discussed using a data based obtain from an experimental photovoltaic amphitheatre of minimum dimension 0.4kV/10kW.

Discrete-time sliding-mode control of four driving/steering wheels mobile platform

Abstract: In this paper a discrete-time sliding mode controller for the trajectory tracking problem of four-driving-steering wheels (4DW/SW) mobile platform. Seekur is a holonomic, all-weather, outdoor robot platform for outdoor security, inspection and research. Seekur has an unique shape that combined with omni-directional steering allows truly holonomic movement. The discrete-time sliding mode controller has been designed using a discrete time nonholonomic model of Seekur, instead of the usual continuous-time model and the problems caused by the discretization of the continuous-time controller are avoided. The efficiency of the discrete-time sliding mode controller is proved by simulations and real time results.

Forcasting of renewable energy load with radial basis function (rbf) neural networks

Abstract: This paper focus on radialbasis function (RBF) neural networks, the most popular and widely-used paradigms in many applications, including renewable energy forecasting. It provides an analysis of short term load forecasting STLF performances of RBF neural networks. Precisely, the goal is to forecast the DPcg (difference between the electricity produced from renewable energy sources and consumed), for shortterm horizon. The forecasting accuracy and precision, in capturing nonlinear interdependencies between the load and solar radiation of these neural networks are illustrated and discussed using a data based obtain from an experimental photovoltaic amphitheatre of minimum dimension 0.4kV/10kW.

Temporal recurrent modelling appllied to manufacturing flexible lines served by collaborative robots

Abstract: This article proposes a temporal recurrent approch of hierarchical systems modeling, symplifing prevoius tools in thies area of th authors. The states of the systems are supposed known for system functioning at every occurence moment. In addition to them, appear external events for nonautonomus system sysncronisation {s i }, with transitions in Temporised Recurrent Petri Nets (TRecPN) model. The sysncronised signals are defined on an assembly of subsets, conditioned by the moment of occurence and the temporal interval when are expected in network. This approch permits an hierarchical approch on levels of Petri Net model. The refining process of the model is made on horisontal. In each place is a PN model, each one is linked with a distinct temporal interval represented by a syncronised signals subset. In an explected syncronised signal doesn't appears, the model functioning will be stoped. Each level is linked with a LIFO object placed on a lower level dedicated to the transfer of the last state reache by the system. In this context, two type of applications are proposed: a) recurrent detection function modelling; b) manufacturing system served by colaborative robots support.

Discrete-time sliding-mode control of four driving-steering wheels autonomous vehicle

Abstract: A discrete-time sliding-mode control for the trajectory tracking problem of four driving-steering wheels (4DW/SW) autonomous vehicle SEEKUR is presented in this paper SEEKUR is a holonomic, all-weather, outdoor robot platform for outdoor security, inspection and research SEEKUR's unique shape and omni-directional steering allow truly holonomic movement A discrete-time nonholonomic model of SEEKUR is used for the design of the controller, instead of the usual continuous-time model, thus avoiding problems caused by the discretization of the continuous-time controller The effectiveness of the proposed controller is proven by simulation results

Discrete-Time Sliding-Mode Control of a Mobile Platform with Four Driving/Steering Wheels

Abstract: In this paper the problem of trajectory tracking of the four-driving/steering wheels (4DW/SW) mobile platform SEEKUR, by means of a discrete-time sliding mode controller is presented. SEEKUR is a mobile platform which may be assimilated as an autonomous vehicle. Commercially available, both holonomic and nonholomic, all-weather, outdoor autonomous vehicle platform suitable for a wide range of security, military inspection and research applications. The discrete-time sliding-mode controller has been designed using a discrete time nonholonomic model of SEEKUR. Simulation and real-time results are presented in trajectory tracking control.

Control and Obstacle Avoidance of a Mobile Platform Used as Robotic Assistant for Elderly and Disabled

Abstract: In this paper a fuzzy control and an obstacle avoidance system, together with a distributed system of embedded microcontrollers, are presented. In the real-time control, a wheeled mobile robot (WMR), Pioneer 3-DX, from Mobile Robots, has been used. The solution adopted can be easily ported for the implementation of an intelligent wheelchair, capable either to carry an elderly or disabled person, or to move independently in a smart environment, as a sensorial extension of the assisted individual. A number of control modules are located on the mobile robot, while others are deployed in an intelligent environment. This solution can significantly reduce the cost of developing a robotic assistant for the elderly and disabled. The structure of the real-time setup is described in detail, as well as the main algorithms used for each individual task: path following, obstacle avoidance, data acquisition. Also, an obstacle avoidance system, based on ricochet method, named "the bubble rebound method", is presented. This method is tested only by simulation.