• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.164-172
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• 2019

In this paper, we implement a wheeled mobile robot that accurately and autonomously finds the optimal route from the starting point to the destination point based on computer vision in a complex indoor environment. We get a number of waypoints from the starting point to get the best route to the target through deep reinforcement learning. However, in the case of autonomous driving, the majority of cases do not reach their destination accurately due to external factors such as surface curvature and foreign objects. Therefore, we propose an algorithm to deepen the waypoints and destinations included in the planned route and then correct the route through the waypoint recognition while driving to reach the planned destination. We built an autonomous wheeled mobile robot controlled by Arduino and equipped with Raspberry Pi and Pycamera and tested the planned route in the indoor environment using the proposed algorithm through real-time linkage with the server in the OSX environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.129-138
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• 2004

In this paper, we propose a method to apply a decentralized control algorithm for passive velocity field control using virtual flywheel system to cooperative 3-wheeled mobile robots, and these subsystem are under nonholonomic constraints. The considered robotic systems convey a common rigid object in a horizontal plain. Moreover we will proof the passivity and robustness for cooperative mobile robotic systems with decentralized passive velocity field control. Finally, The effectiveness of proposed control algorithm is examined by numerical simulation for cooperation tasks with 3-wheeled mobile robot systems.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.172-180
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• 2006

본 논문은 Dijkstra 알고리즘에 기초한 최단거리 경로계획을 하며 이 경로를 추적하기 위한 슬라이딩 모드 제어를 제시한다. 슬라이딩 모드 제어기는 동적매개변수 불확실성과 입력외란이 존재 시에도 강인 점근적으로 계획된 경로를 추적하도록 한다. 더불어 작업장 내의 이동로봇의 위치를 USB 카메라에 의해 감지하며, Pin-hole 카메라모델로 하여 카메라에 의해 관측되는 작업장 내의 이륜구동로봇의 위치좌표를 결정하였으며, 이 위치를 정확히 감지하기 위해 Tsai법을 사용하여 카메라 보정한다. 시뮬레이션 결과는 슬라이딩 모드 제어기의 성능을 검증하기 위해 보였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.201-202
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• 2020

본 논문에서는 이륜 자동 균형 로봇을 제작하는데 초점을 맞추고 있다. 키워드는 아두이노와 PID컨트롤이다. 아두이노를 사용하여 로봇을 전체적으로 제어하였고 PID컨트롤로 로봇이 스스로 균형을 잡을 수 있도록 한다. 두 바퀴를 이용해 넘어지지 않고, 밸런스를 잡을 수 있도록 로봇의 바퀴, 프레임, 스텝모터, 드라이버 등을 구성하였고, 향후 이륜 자동 균형 로봇이 자유롭게 움직일 수 있도록 PID 정밀 제어를 하게 될 것이다.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.826-832
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• 2016

A two-wheeled balancing mobile robot (TWBMR) has the characteristics of both nonlinear and underactuated system. In this paper, the disturbances acting on a TWBMR are classified into body disturbance and wheel disturbance. Additionally, we describe a nonlinear disturbance observer, which is suitable as a single input multi-output (SIMO) system for the longitudinal motion of TWBMR. Finally, we propose a reasonable disturbance compensation technique that combines the indirect reference input of equilibrium point and the direct torque compensation input. Simulations and experimental results show that the proposed disturbance compensation method is an effective way to achieve robust postural stability, specifically on inclined terrains.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1933-1938
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• 2003

A covariance matrix is a tool that expresses odometry uncertainty of the wheeled mobile robot. The covariance matrix is a key factor in various localization algorithms such as Kalman filter, topological matching and so on. However it is not easy to acquire an accurate covariance matrix because we do not know the real states of the robot. Up to the authors knowledge, there seems to be no established result on the covariance matrix estimation for the odometry. In this paper, we propose a new method which can estimate the covariance matrix from empirical data. It is based on the PC-method and shows a good estimation ability. The experimental results validate the performance of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.58-65
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• 2003

In this paper, a new model, which is a Takagi-Sugeno fuzzy model, for mobile robot is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and the outer loop is a PI controller designed for tracking the reference input, is suggested. Because the robot dynamics is nonlinear, it requires the controller to be insensitive to the nonlinear term. To achieve this objective, the model is developed by well known T-S fuzzy model. The design algorithm of inner state-feedback loop is regional pole-placement. In this paper, regions, for which poles of the inner state feedback loop are lie in, are formulated by LMI's. By solving these LMI's, we can obtain the state feedback gains for T-S fuzzy system. And this paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ(linear quadratic) cost. By using these properties, it is also shown in this paper that the PI controller can be obtained by solving the LQ problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1448-1456
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• 1999

In this paper, we propose a new technique for path-following of the wheeled mobile robot systems with nonholonomic constraints using a path-observer. We discuss the path-following problems of the nonholonomic mobile robot systems which have two nonsteerable, independently driven wheels with the various initial conditions such as a position, a heading angle, and a velocity. It is shown that the performance of dynamic path-following importantly is affected by the intial conditions. Particularly, if the initial conditions become more distant from the desired path and the desired velocity become faster, the system is shown to have worse performance and small time local stable. To find the controllable and stable control for path-following with various initial configuration, we propose the path-observer which can be used for control of the stable path-following of nonholonomic mobile robot system with the various initial conditions. The proposed scheme exhibits the efficient path-following properties for nonholonomic mobile robot in any intial conditions. The simulation results demonstrate the effectiveness of the proposed method for dynamic path-following tasks with the various initial conditions.

• International Journal of Automotive Technology
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• v.6 no.5
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• pp.545-554
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• 2005

Passive velocity field control (PVFC) was previously developed for fully mechanical systems, in which the motion task was specified by behaviors in terms of a velocity field and the closed-loop was passive with respect to the supply rate given by the environment input. However, the PVFC was only applied to a single manipulator. The proposed control law was derived geometrically and the geometric and robustness properties of the closed-loop system were also analyzed. In this paper, we propose a virtual passivity-based algorithm to apply decentralized control to multiple 3­wheeled mobile robotic systems whose subsystems are under nonholonomic constraints and convey a common rigid object in a horizontal plain. Moreover, it is shown that multiple robot systems ensure stability and the velocities of augmented systems converge to a scaled multiple of each desired velocity field for cooperative mobile robot systems. Finally, the application of proposed virtual passivity-based decentralized algorithm via system augmentation is applied to trace a circle and the simulation results is presented in order to show effectiveness for the decentralized control algorithm proposed in this research.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.689-696
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• 2000

In this paper we propose an eminent controller for wheeled mobile robots. This controller consists of an input-output linearization controller trying to stabilize the system and a neural network controller to compensate for uncertainties. The uncertainties are divided into two parts. First unstructured uncertainties include the elements related with system order such as friction disturbance. Second structure uncertainties are the incorrect system parameters A neural network structure of the proposed overall controller learns structural errors of the wheeled mobile robots with uncertainties and includes the neural network output. This controller learns quickly the model and has good tracking performance Simulation results show that the proposed controller is more efficient than analog controllers.