Design of test track for accurate calibration of two wheel differential mobile robots

Jung, Changbae; Moon, Chang Bae; Jung, Daun; Choi, Jong Suk; Chung, Woojin

doi:10.1007/s12541-013-0305-6

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…In a vehicle working under fixed, constant load, the correction of systematic errors only required the application of one of the methods described in papers (Borenstein and Feng 1996;Chong and Kleeman 1997;Jung et al 2014). Such methods enable the determination of wheel effective radiuses upon the final correction of the position.…”

Section: Resultsmentioning

confidence: 99%

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The impact of load on the wheel rolling radius and slip in a small mobile platform

2019

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Automated guided vehicles are used in a variety of applications. Their major purpose is to replace humans in onerous, monotonous and sometimes dangerous operations. Such vehicles are controlled and navigated by application-specific software. In the case of vehicles used in multiple environments and operating conditions, such as the vehicles which are the subject of this study, a reasonable approach is required when selecting the navigation system. The vehicle may travel around an enclosed hall and around an open yard. The pavement surface may be smooth or uneven. Vehicle wheels should be flexible and facilitate the isolation and absorption of vibrations in order to reduce the effect of surface unevenness to the load. Another important factor affecting the operating conditions are changes to vehicle load resulting from the distribution of the load and the weight carried. Considering all of the factors previously mentioned, the vehicle's navigation and control system is required to meet two opposing criteria. One of them is low price and simplicity, the other is ensuring the required accuracy when following the preset route. In the course of this study, a methodology was developed and tested which aims to obtain a satisfactory compromise between those two conflicting criteria. During the study a vehicle made in Technical University of Rzeszow was used. The results of the experimental research have been analysed. The results of the analysis provided a foundation for the development of a methodology leading to a reduction in navigation errors. Movement simulations for the proposed vehicle system demonstrated the potential for a significant reduction in the number of positioning errors.

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Section: Resultsmentioning

confidence: 99%

“…The calibration of non-systematic errors was the research area of authors (Chong and Kleeman 1997) and (Jung et al 2014). Those studies used the model UMBmark, with further modifications implemented by the authors.…”

Section: Related Workmentioning

confidence: 99%

The impact of load on the wheel rolling radius and slip in a small mobile platform

2019

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“…The simplified kinematics model of two-wheel differential AGV is shown in Figure 4. 40,41 The left and right motors of AGV are driven independently, and the centroid is at the midpoint of the two wheels on the central axis of the chassis. Therefore, the kinematics model of AGV can be simplified as a simple geometric motion problem.…”

Section: Agv Control Modelmentioning

confidence: 99%

Research on AGV trackless guidance technology based on the global vision

Zheng

2022

Science Progress

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With the change of manufacturing mode and the progress of science and technology, the traditional manufacturing industry has gradually developed to intelligent manufacturing and flexible manufacturing. To achieve factory transformation, Automatic Guided Vehicle (AGV) is indispensable. In this paper, an AGV trackless guidance technology based on global vision is proposed. Firstly, the global vision camera is used to obtain the image of the AGV driving area, and then the obstacle information and position information of the AGV are obtained by image processing technology. Secondly, the A* algorithm is used to intelligently plan the AGV driving path, and the wireless network communication is used to control the AGV driving according to the planned path. Experiments show that the method is feasible and has the advantages of high flexibility, high precision, low cost and strong expansibility, which is of great significance to the realization of intelligent warehouse and unmanned chemical plant.

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“…So some good methods should be adopted in order to obtain a good effect. So far, there are many researches on the mobile robot tracking control strategy [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Research on Open-Closed-Loop Iterative Learning Control with Variable Forgetting Factor of Mobile Robots

Wang

Dong

Wang

2016

Discrete Dynamics in Nature and Society

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We propose an iterative learning control algorithm (ILC) that is developed using a variable forgetting factor to control a mobile robot. The proposed algorithm can be categorized as an open-closed-loop iterative learning control, which produces control instructions by using both previous and current data. However, introducing a variable forgetting factor can weaken the former control output and its variance in the control law while strengthening the robustness of the iterative learning control. If it is applied to the mobile robot, this will reduce position errors in robot trajectory tracking control effectively. In this work, we show that the proposed algorithm guarantees tracking error bound convergence to a small neighborhood of the origin under the condition of state disturbances, output measurement noises, and fluctuation of system dynamics. By using simulation, we demonstrate that the controller is effective in realizing the prefect tracking.

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Design of test track for accurate calibration of two wheel differential mobile robots

Cited by 10 publications

References 12 publications

The impact of load on the wheel rolling radius and slip in a small mobile platform

The impact of load on the wheel rolling radius and slip in a small mobile platform

Research on AGV trackless guidance technology based on the global vision

Research on Open-Closed-Loop Iterative Learning Control with Variable Forgetting Factor of Mobile Robots

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