Dynamic modeling and construction of a two-wheeled mobile manipulator, part I: Self-balancing

Ebrahimi, Saeed; Mardany, Arman

doi:10.1109/icrom.2015.7367778

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…A two-RLM on a mobile robot was also modelled by the kinematic technique in Ref. [96]. And the authors improved the mobile robot to climb obstacles as discussed in Ref.…”

Section: Kinematic Methodsmentioning

confidence: 99%

A critical review of modelling methods for flexible and rigid link manipulators

Lee

Alandoli

2020

J Braz. Soc. Mech. Sci. Eng.

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Mathematical modelling plays an important role for robotic manipulators in order to design their particular controllers. Also, it is hard challenge to obtain an accurate mathematical model or obtain a suitable modelling method in such vast field. Thus, this critical review is advantageous and indispensable for researchers who are interested in the area to gain fruitful knowledge on the mathematical modelling methods. This paper is classified based on the type of robotic manipulators such as flexible link manipulators (FLMs), rigid link manipulators (RLMs) and hybrid manipulators which involves rigid links and flexible links. The used modelling methods for FLMs are the assumed mode method, the finite element method, and the lumped parameter method as approximation techniques which are well explained and reviewed. The Lagrangian method has inclusive explanation and review which is widely participated for obtaining the dynamic equations of FLMs, and it is appropriate and commonly employed for modelling RLMs. The Newtonian method, the forward kinematic, and the inverse kinematic are also well discussed and reviewed which are suitable and commonly employed for modelling RLMs. The critical discussion of 170 articles reported in this paper guides researchers to select the suitable method for modelling. This paper reviews the published articles in the period of 2010-2020 except for few older articles for the need of providing essential theoretical knowledge. The advantages and disadvantages of each method are well summarized at the end of the paper. The intelligent identification methods are briefly discussed due to the lack of publications especially on the period of 2010-2020.

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“…A two-RLM on a mobile robot was also modelled by the kinematic technique in Ref. [96]. And the authors improved the mobile robot to climb obstacles as discussed in Ref.…”

Section: Kinematic Methodsmentioning

confidence: 99%

A critical review of modelling methods for flexible and rigid link manipulators

Lee

Alandoli

2020

J Braz. Soc. Mech. Sci. Eng.

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“…The tilt angle velocity and the tilt angle are collected by the sensor, and the Kalman filter optimal estimation method is used to fuse the two parameters to eliminate the drift caused by the system noise, so it can output the dynamic optimal angle value, and then calculate the angle to obtain the restoring force. The system upright process is like the inverted pendulum movement, it does not immediately return to the original vertical state once tilted, and needs to swing until it is balanced [3][4][5], so damping force is needed to speed up the system to maintain the upright balance, which is a differential D process. The tilt angular velocity is acquired by the sensor, and the angular velocity differential operation is performed to obtain the damping force.…”

Section: Balance Control Principlementioning

confidence: 99%

The Design of Two-Wheeled Robotic Self-Balancing Walking Control System

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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Research on mobile robots has become a popular field in robot research because of the broad application prospects of mobile robots in all walks of life. Considering the complicated designs and high prices of the Humanoid robots' different DoF (Degree of Freedom), a two-wheeled robotic self-balancing walking control system is designed in the paper. The system uses the microcontroller as the control core, the attitude sensor to collect the angular velocity and acceleration data, and the Kalman filter to perform data fusion to obtain the optimal inclination and to realize the tilt control. It also uses the encoder to measure the walking speed to realize the speed control in the front and rear direction. The steering control of the robot is realized by the rotational difference between the two motors. The experiment proves that the two-wheeled robot can walk upright and keep balance, and has the advantages of simple structure, convenient parameter adjustment and low cost.

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“…It twists right or left by the minimum deviance of handle.The technology and process that introduces this kind of movement is called dynamic stability (Wang, Lu, & Hou, 2015). Describing the robot states, there are mathematic relations (Ebrahimi & Mardany, 2015). In segway system, two parameters should be controlled that are balance and rotation deflection.…”

Section: Introductionmentioning

confidence: 99%