Inertial navigation system for an automatic guided vehicle with Mecanum wheels

Kim, Jungmin; Woo, Seung-Beom; Kim, Jae-Yong; Do, Joo-Cheol; Kim, Sungshin; Bae, Sun-Il

doi:10.1007/s12541-012-0048-9

Cited by 44 publications

(22 citation statements)

References 8 publications

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“…Udomsaksenee et al [35] proposed a global control method for Mecanum-wheeled vehicles with slip compensation.The latest research on cooperative transportation mainly focuses on path planning and navigation algorithms in working environments, and control methods in the cooperative transportation process. Research on the Mecanum-wheeled robot platform is mainly focused on single-Mecanum-wheeled robots [8,9,[36][37][38][39], while there is less research on the kinematic of a combination system and motion compensation of multiple-Mecanum-wheeled robot platforms. However, studying the kinematic and characteristics of the combined omnidirectional mobile system is the basis for studying the motion control, path planning, and navigation of the combination system.…”

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confidence: 99%

Kinematic Modeling of a Combined System of Multiple Mecanum-Wheeled Robots with Velocity Compensation

Dai

et al. 2019

Sensors

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In industry, combination configurations composed of multiple Mecanum-wheeled mobile robots are adopted to transport large-scale objects. In this paper, a kinematic model with velocity compensation of the combined mobile system is created, aimed to provide a theoretical kinematic basis for accurate motion control. Motion simulations of a single four-Mecanum-wheeled virtual robot prototype on RecurDyn and motion tests of a robot physical prototype are carried out, and the motions of a variety of combined mobile configurations are also simulated. Motion simulation and test results prove that the kinematic models of single-and multiple-robot combination systems are correct, and the inverse kinematic correction model with velocity compensation matrix is feasible. Through simulations or experiments, the velocity compensation coefficients of the robots can be measured and the velocity compensation matrix can be created. This modified inverse kinematic model can effectively reduce the errors of robot motion caused by wheel slippage and improve the motion accuracy of the mobile robot system.Sensors 2020, 20, 75 2 of 37 robot called MC-Drive, and the MC-Drive TP200 robot has been used to carry aircraft at Airbus manufacturing plants [13,14]. The KUKA omniMove UTV-2 set is a heavy-duty mobile platform with 12 Mecanum wheels that can be used to carry large objects [15]. (2) Using a combination of multiple Mecanum-wheeled robot platforms, which can be considered as a whole with cooperative omnidirectional motion and transport. Usually, mobile platforms used for cooperative transportation are symmetrically arranged. For example, a railcar body can be carried cooperatively by four KUKA omniMove mobile platforms at the Siemens plant in Krefeld, Germany [16]. The four mobile platforms are symmetrically arranged at four corners of the railcar body. Omni-directional mobile platforms with 8, 12, 16, or 32 Mecanum wheels can also be considered as specific combinations of multiple basic mobile platforms.The mature basic theory of four-Mecanum-wheeled robots is the basis of research on multi-robot systems. Muir [17][18][19] carried out basic research on Mecanum-wheeled robots and developed a kinematic and dynamic model and control on a four-Mecanum-wheeled robot. Campion et al. [20] studied structural properties and classification of kinematic and dynamic models of mobile wheeled robots and derived a motion constraint equation of a Mecanum wheel that can be used in kinematic research of multiple Mecanum-wheeled robots. Robots with four or more Mecanum wheels are overactuated systems with one or more motion constraints (wheel velocities are linearly correlated). Every additional wheel, and every additional robot, adds new motion constraints. So, the motion constraints of a multiple-Mecanum-wheeled robot system can be developed [21], which is also valid for multi-robot systems. The problem of transporting objects with a combined system is also a typical cooperative object transport problem in multi-robot systems, which is a growing rese...

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Kinematic Modeling of a Combined System of Multiple Mecanum-Wheeled Robots with Velocity Compensation

Dai

et al. 2019

Sensors

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“…그리고 유선 항법 시 스템은 매설된 유도선을 인식하기 위한 장치와 바닥과의 거 리가 매우 가깝기 때문에 서스펜션에 의해 장치가 파손될 가능성이 매우 높다 [7][8][9][10]. DGPS 또는 카메라 등을 이용한 시각 센서 기반 주행 시스템과 같은 실외에서도 사용이 가 능한 항법 시스템이 존재하지만 이는, 오차 범위가 매우 크 거나, 연산이 매우 복잡하다는 단점으로 인해 안전성이 크 게 요구되는 산업 현장의 무인운반차에 적용하기에는 비효 율적이다 [11][12][13].…”

Section: 서 론unclassified

Development of Magnet Position Device for Outdoor Magnet Guidance Vehicle

Cho¹,

Kim²

2014

Journal of Korean Institute of Intelligent Systems

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This paper is research paper on the MPD(Magnet Position Device) for the outdoor MGV(Magnet /Magnet Gyro Guidance Vehicle). Usually, MGV is used in indoor environment because of a measurement height of the magnet position device. CMPD(Commercial magnet position device) has 30 mm measurement height, so this is suitable structure in indoor environment like to a flat surface. Outdoor environment is an uneven and irregular, So Outdoor MGV must has a suspension. But CMPD is unsuitable for outdoor environment because of a collision with a surface caused by suspension. Thus, measurement height of the outdoor MPD is positively necessary more than 100 mm. So, we suggest the outdoor MPD using analog magnet hall sensor, moving average filter and Characteristic(rate of the magnet hall sensor) function of the localization. Result of the experiments, the proposed Magnet Position Device for the outdoor MGV has localization accuracy 4.31 mm, measurement height 150 mm and width 150 mm and is efficient more than CMPD.

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“…They provide the omnidirectional ability to move instantaneously in any direction from any configuration without changing the direction of the wheel. This kind of mobile robot with four degrees of freedom (DOFs) has been used in vast applications instead of conventional vehicles due to its flexible mobility in performing difficult tasks in congested environments with complex obstacles [23,24]. To date, the omni-Mecanum-wheeled vehicles have been widely used in nursing-care robots, intelligent wheelchairs, industrial robots, and nursing-care robots [23,24].…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles

et al. 2019

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This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.

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Inertial navigation system for an automatic guided vehicle with Mecanum wheels

Cited by 44 publications

References 8 publications

Kinematic Modeling of a Combined System of Multiple Mecanum-Wheeled Robots with Velocity Compensation

Kinematic Modeling of a Combined System of Multiple Mecanum-Wheeled Robots with Velocity Compensation

Development of Magnet Position Device for Outdoor Magnet Guidance Vehicle

FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles

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