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CONTENTS
Volume 1, Number 1, January 2014
 

Abstract
Microgripper is an essential device in the micro-operation system. It can convert other types of energy into mechanical energy and produce clamp movement with required chucking force, which enables it a broad application prospect in the domain of tiny components

Key Words
microgripper; actuator; sensor; mechanism; control

Address
Wenji Ai and Qingsong Xu: Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macao, China

Abstract
Due to the rapid progress in the field of robotics, it is a high time to concentrate on the development of a robot that can manoeuvre in all type of landscapes, ascend and descend stairs and sloping surfaces autonomously. This paper presents details of a prototype robot which can navigate in very rough terrain, ascend and descend staircase as well as sloping surface and cross ditches. The robot is made up of six differentially steered wheels and some passive mechanism, making it suitable to cross long ditches and landscape undulation. Static stability of the developed robot have been carried out analytically and navigation capability of the robot is observed through simulation in different environment, separately. Description of embedded system of the robot has also been presented and experimental validation has been made along with some details on obstacle avoidance. Finally the limitations of the robot have been explored with their possible reasons.

Key Words
All Terrain Robot (ATR); passive compliance mechanism; static force analysis; embedded systems; automation; simulation; real experiments

Address
Debesh Pradhan: Fluid Section & Piping Division, MECON Ltd., Ranchi, India
Jishnu Sen: Department of Environmental Control System & Life System, HAL, Banglore, India
Nirmal Baran Hui: Department of Mechanical Engineering, NIT Durgapur, West Bengal, India


Abstract
This paper deals with the problem of steering a group of mobile robots along a reference path while maintaining a desired geometric formation. To solve this problem, the overall formation is decomposed into numerous geometric patterns composed of pairs of robots, and the state of the geometric patterns is defined. A control algorithm for the problem is proposed based on the Nash equilibrium strategies incorporating receding horizon control (RHC), also known as model predictive control (MPC). Each robot calculates a control input over a finite prediction horizon and transmits this control input to its neighbor. Considering the motion of the other robots in the prediction horizon, each robot calculates the optimal control strategy to achieve its goals: tracking a reference path and maintaining a desired formation. The performance of the proposed algorithm is validated using numerical simulations.

Key Words
nash equilibrium; geometric pattern formation (GPF); formation control; nonholonomic mobile robots; receding horizon control (RHC); model predictive control (MPC)

Address
Seung-Mok Lee, Hanguen Kim, Serin Lee and Hyun Myung: Urban Robotics Laboratory, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Korea

Abstract
This paper presents theoretical and experimental investigations into the dynamic modelling and characterisation of a two-link flexible manipulator incorporating payload. A planar two-link flexible manipulator that moves in a horizontal plane is considered. A dynamic model of the system is developed using a combined Euler-Lagrange and assumed mode methods, and simulated using Matlab. Experiments are performed on a lab-scaled two-link flexible manipulator for validation of the dynamic model and characterisation of the system. Two system responses namely hub angular position and deflection responses at both links are obtained and analysed in time and frequency domains. The effects of payload on the dynamic characteristics of the flexible manipulator are also studied and discussed. The results show that a close agreement between simulation and experiments is achieved demonstrating an acceptable accuracy of the developed model.

Key Words
assumed mode; dynamic characterisation; experiment; modelling; two-link flexible manipulator

Address
M. Khairudin: Department of Electrical Engineering, Universitas Negeri Yogyakarta, Indonesia
Z. Mohamed, A.R. Husain and R. Mamat: Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Malaysia

Abstract
This paper contributes towards the development of a computer vision system for telemonitoring of industrial articulated robotic arms. The system aims to provide precision real time measurements of the joint angles by employing low cost cameras and visual markers on the body of the robot. To achieve this, a mathematical model that connects image features and joint angles was developed covering rotation of a single joint whose axis is parallel to the visual projection plane. The feature that is examined during image processing is the varying area of given circular target placed on the body of the robot, as registered by the camera during rotation of the arm. In order to distinguish between rotation directions four targets were used placed every 90

Key Words
industrial robot; pose monitoring; industrial computer vision; area features

Address
Aris Karagiannidis and George C. Vosniakos: School of Mechanical Engineering, National Technical University of Athens, Heroon Polytechniou 9, 157 80 Athens, Greece

Abstract
In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot

Key Words
neural networks; mobile robot control; autonomous robots; obstacle avoidance; reactive behavior

Address
Poramate Manoonpong and Florentin Wörgötter: Bernstein Center for Computational Neuroscience (BCCN), the Third Institute of Physics, Georg-August-Universität Göttingen, D-37077 Göttingen, Germany
Pudit Laksanacharoen: Mechanical and Aerospace Engineering Department, Faculty of Engineering, King Mongkut


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