• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.241-246
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• 2004

This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.19-24
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• 1992

Real-time mobile robot controllers usually have been designed with an emphasis on control theory ignoring the importance of system integration. This paper demonstrates that useful mobile robots require a real time controller with a wide range of capabilities in addition to control theory. These capabilities include: path-planning, position estimation, path tracking control and wheel control. An architectural framework supporting these capabilities has been designed and implemented. Using this frame work, individual modules such as a path planner, a path tracking controller, position estimators, wheel controllers and other cruical elements have been successfully integrated into the control system for the LCAR robot which was developed as a proto-type mobile robot in our laboratory. The context of the research, the architecture, its implementation and performance results from experiments are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.515-526
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• 2003

Tutorial contents of kinematics and dynamics of a wheeled drive mobile robot are presented. Based on the dynamic model, simulation studies of position tracking of a mobile robot are performed. The control structure of several position control algorithms using visual feedback are proposed and their performances are compared. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position control schemes are proposed. Experiments are conducted and the results show the performance of the vision based neural network control scheme fumed out to be the best among several proposed schemes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.154-161
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• 2012

This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1817-1825
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• 2021

Omnidirectional mobile robots can be mobile in any direction without changing the robot's direction, making them easy to apply in many applications and providing excellent maneuverability. Omnidirectional mobile robots have non-linear dynamic components such as friction, making them difficult to model accurately. In this paper, we linearize the mobile robot system using the mobile robot's inverse dynamics and integral sliding mode control method to remove these nonlinear components. And the position and velocity gains are optimized using a genetic algorithm to realize the optimal performance of the proposed system control method. As a result of the performance evaluation, the genetic algorithm's control method showed superior performance than the control method with an arbitrary gain. And the proposed inverse dynamic and integral sliding mode control method can be applied to other control methods. It can be beneficial for designing a linear control system.

• Journal of information and communication convergence engineering
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• v.3 no.1
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• pp.33-37
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• 2005

One of the most important feature of the Mobile Manipulator is redundant freedom. Using the redundant freedom, Mobile Manipulator can move various mode, perform dexterous motion. In this paper, to improve robot job ability, as two robots perform a job in co-operation control, we studied optimal position and posture of Mobile Manipulator with minimum movement of each robot joint. Kinematics of mobile robot and task robot is solved. Using mobility of Mobile robot, weight vector of robots is determined. Using Gradient methode, global motion trajectory is minimized. so the job which Mobile Manipulator perform is optimized. The proposed algorithm is verified with PURL-II which is Mobile Manipulator combined Mobile robot and task robot. and discussed the result.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.475-475
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• 2000

This paper describes the construction of an autonomous mobile robot with functions of collision avoidance and speech recognition that is used for teaching path of the robot. The human voice as a teaching method provides more convenient user-interface to mobile robot. For safe navigation, the autonomous mobile robot needs abilities to recognize surrounding environment and avoid collision. We use u1trasonic sensors to obtain the distance from the mobile robot to the various obstacles. By navigation algorithm, the robot forecasts the possibility of collision with obstacles and modifies a path if it detects dangerous obstacles. For these functions, the robot system is composed of four separated control modules, which are a speech recognition module, a servo motor control module, an ultrasonic sensor module, and a main control module. These modules are integrated by CAN(controller area network) in order to provide real-time communication.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• ETRI Journal
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• v.19 no.3
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• pp.98-115
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• 1997

The architecture of the CDMA mobile system (CMS) is developed based on three function groups - service resource, service control, and service management groups. In this paper, the CMS architecture is discussed from the point of view of implementing these functions. The variable length packets are used for transmission. The synchronization clock signals are derived form the GPS receiver. The open loop and closed loop techniques are used for the power control. The internationally accepted signaling and network protocols are employed. The call control for the primary services in designed to provide efficient mobile telecommunication services. The softer handoff is implemented in one card. The mobile assisted handoff and the network assisted handoff are employed in the soft and hard handoffs. The authentication is based on the secret data which includes random numbers. The management functions, which include the location management, resource management, cell boundary management and OAM management, are implemented to warrant the system efficiency, maximum capacity and high reliability. The architecture ensures that the CMS is flexible and expandable to provide subscribers with economic and efficient system configuration. The dynamic power control, adaptive channel allocation. and dynamic cell boundary management are recommended for future work.