• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.76.2-76
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• 2002

Because of the wheeled mobile robot is modeled by nonlinear system framework and controlled by nonlinear algorithms or fuzzy algorithms, the treatment of wheeled mobile robot is very complecate and conservative. In this paper, a new model of two wheeled mobile robot, which is a type of linear system and treated easily, is presented. And we will show that the control algorithms based on the linear system theory is well work to the wheeled mobile robot by simulation and experiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.941-948
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• 2022

Disaster response robots are deployed to disaster sites where human access is difficult and dangerous. The disaster response robots explore the disaster sites prevent a structural collapse and perform lifesaving to minimize damage. It is difficult to operate robots in the disaster sites due to rough terrains where various obstacles are scattered, communication failures and invisible environments. In this paper, we developed a series connectable wheeled robot module. The series connectable wheeled robot module was developed into two types: an active driven robot module and a passive driven robot module. A wheeled robot was built by connecting the two active type robot modules and one passive type robot module. Two robot modules were connected by one DoF rotating joint, allowing the wheeled robot to avoid obstructions in a vertical direction. The wheeled robot performed driving and obstacle avoidance using only pressure sensors, which allows the wheeled robot operate in the invisible environment. An obstacle avoidance experiment was conducted to evaluate the performance of the wheeled robot consisting of two active driven wheeled robot modules and one passive driven wheeled robot module. The wheeled robot successfully avoided step-shaped obstacles with a maximum height of 80 mm in a time of 24.5 seconds using only a pressure sensors, which confirms that the wheeled robot possible to perform the driving and the obstacle avoidance in invisible environment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.201-204
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• 2004

In this paper, a direct adaptive tracking controller based Lyapunov method is designed for a wheeled mobile robots. A wheeled mobile robots have three degrees of freedom and two control variables. Therefore, it is difficult to control a mobile robot using the general linear control. We introduce two kinds of Lyapunov function for the design of the controller and verify the controller. A mobile robots using the designed adaptive direct tracking controller is well-behaved and is easily implemented.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.6
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• pp.731-737
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• 1999

This paper describes the path tracking control for a mobile robot which has two casters at the front and rear to keep balance and two driving wheels on the left and right sides of its body. Power wheeled steering method is adapted to control heading of the robot. It is very difficult to find appropriate feedback gains when linear regulator control scheme is adapted to path tracking con-trol of this type of robot. Therefore in this paper we propose the path tracking control algorithm using the fuzzy logic control scheme for this type of root. Simulation to prove the validity of the proposed two algorithms is performed. The results are reported as last part in this paper.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2472-2474
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• 2002

This paper describe a trajectory generation method for a two-wheeled mobile robot using cubic Bezier curve. It is proposed that the method to determine the location of control points which mainly affect the shape of curve, and constrains for two-wheeled mobile are examined. Simulation results show its traceability of the trajectory of mobile robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.652-658
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• 2010

This paper presents the implementation and control of a two wheeled mobile robot(TWMR) based on a balancing mechanism. The TWMR is a mobile inverted pendulum structure that combines an inverted pendulum system and a mobile robot system with two arms instead of a rod. To improve robustness due to disturbances, the radial basis function (RBF) network is used to control an angle and a position at the same time. The reference compensation technique(RCT) is used as a neural control method. Experimental studies are conducted to demonstrate performance of neural network controllers. The robot are implemented with the remote control capability.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1037-1043
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• 2011

Two-wheeled balancing mobile robots are currently controlled in terms of linear control methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and greatly influence the overall driving performance. This paper addresses the SDRE nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the SDRE control outperforms LQR in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the SDRE control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly contributes to the driving performance and stability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.228-236
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• 2012

In this paper, a controller for two wheeled inverted pendulum robot is designed to have more stable balancing capability than conventional controller. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the controller are obtained for specified 3 users' weights using trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the user's weight is arbitrarily selected. Through the simulation study we find that the designed fuzzy controller using the neural network is superior to the conventional fuzzy controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.432-439
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• 2012

In this paper, instead of the conventional PD controller for balancing control of two wheeled inverted pendulum robots, an improved PD controller using the neural network is proposed and implemented for performance verification. First, a two wheeled inverted pendulum robot system is constructed for experiment. Next proper gains of the conventional PD controller according to users' weights are obtained for balancing the robot by use of the trial and error method. The PD gains based on the trial and error method are generalized through the neural network. Experiment results show that the PD controller based on the neural network has better performance than the conventional PD controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.