Intuitive dynamic modeling and flatness-based nonlinear control of a mobile robot

Sahoo, Sauvagya Ranjan; Chiddarwar, Shital S.; Alakshendra, Veer

doi:10.1177/0037549717741192

Cited by 19 publications

(13 citation statements)

References 33 publications

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“…Hence, in mobile robots usually the velocity level kinematics is taken into consideration. The kinematic relationship of the holonomic mobile robot under consideration has been well studied in many papers [20,21]. Here, in order to give a complete framework, we summarize these results referring to the variables shown in Figure 1.…”

Section: Kinematicsmentioning

confidence: 99%

A multiple sensor fusion based drift compensation algorithm for mecanum wheeled mobile robots

Al-Hababi¹,

Ezim²,

Canbek³

et al. 2021

Turk J Elec Eng & Comp Sci

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This paper investigates a multiple sensor fusion based drift compensation technique for a mecanum wheeled mobile robot platform. The mobile robot is equipped with high precision encoders integrated to the wheels and four accelerometers placed on its chassis. The proposed algorithm combines the information from the encoders and the acceleration sensors to estimate the total drift in the acceleration dimension. The inner loop controller is designed utilizing a disturbance observer based acceleration control structure which is blind against the slipping motion of the wheels. The estimated drift acceleration from the sensor fusion is then mapped back to the joint space of the robot and used as additional compensation over the existing controllers. The proposed algorithm is tested on a series of experiments. The results of the experiments are also compared with a recent study in order to provide a benchmark evaluation. The enhanced tracking performance yielding towards smaller error magnitudes in the experiments illustrate the efficacy and success of the proposed control architecture in attenuating the positioning drift of mecanum wheeled robots.

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Section: Kinematicsmentioning

confidence: 99%

A multiple sensor fusion based drift compensation algorithm for mecanum wheeled mobile robots

Al-Hababi¹,

Ezim²,

Canbek³

et al. 2021

Turk J Elec Eng & Comp Sci

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“…Description : Neglecting the model uncertainties and frictions, the dynamic model is given in the robot local frame by the following equations: (see [19] for more details)…”

Section: Variablementioning

confidence: 99%

4-mecanum wheeled mobile robot actuator fault detection & isolation using unknown input observer-based approach

Mellah

Graton

Adel

et al. 2020

2020 European Control Conference (ECC)

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This paper proposes an approach for actuator fault detection & isolation (FDI) in a four mecanum wheeled mobile robots (4-MWMRs). The approach is based on a bank of unknown input observers (UIO) for linear parameter varying (LPV) systems. The FDI is challenging by considering faults with small amplitude and measurements with noise. Added to that, and considering the robot closed-loop control, the faults are compensated and they cannot be detected without a robust FDI algorithm. The objective is to detect and isolate actuator faults before the robot closed-loop deteriorates and leads to an unacceptable extent. keywords: 4-mecanum wheeled mobile robot, dynamic model, actuator faults. *Research leading to these results has received funding from the EU ECSEL Joint Undertaking under grant agreement n 737459 (project Pro-ductive4.0) and from the partners national funding authorities DGE.

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“…Figure 2 shows the robot and the coordinate frames for its four wheels, O cwi ( i = 1 , 0.25em 2 0.25em , 3 0.25em , 4 ) . The relationship between the robot velocity vector, P · crxy = [ x · cr , y · cr , θ · cr ] T , in the P crxy coordinate frame (i.e., the moving frame) and the angular velocity of each wheel θ · ci ( i = 1 , 0.25em 2 0.25em , 3 0.25em , 4 ) is given as 32 :…”

Section: Kinematics and Dynamics Of The Robotmentioning

confidence: 99%

“…While describing this method is beyond the scope of this manuscript, interested readers are requested to refer to Sahoo et al for a detailed explanation. 32…”

Section: Kinematics and Dynamics Of The Robotmentioning

confidence: 99%

“…28 An electrohydraulic fuel control unit for jet engines was tested through HIL simulations by Montazeri-Gh and Nasiri, 29 while a fuel control unit was tested through HIL simulations by Hashemi et al 30 Sisle and McCarthy developed a HIL simulation test for an active missile. 31 In our previous work, 32 we used a bond graph-based technique and a flatness-based control scheme to perform SIL simulations before real-time tests. In the present work, we employed HIL simulations in the case of a physical omnidirectional mobile robot and embedded the robot, its Kinect-based vision system, and Arduino microcontroller in the simulation environment in order to analyze the control strategies and performance of the robot.…”

Section: Introductionmentioning

confidence: 99%

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Flatness-based control scheme for hardware-in-the-loop simulations of omnidirectional mobile robot

Sahoo

Chiddarwar

2019

SIMULATION

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Omnidirectional robots offer better maneuverability and a greater degree of freedom over conventional wheel mobile robots. However, the design of their control system remains a challenge. In this study, a real-time simulation system is used to design and develop a hardware-in-the-loop (HIL) simulation platform for an omnidirectional mobile robot using bond graphs and a flatness-based controller. The control input from the simulation model is transferred to the robot hardware through an Arduino microcontroller input board. For feedback to the simulation model, a Kinect-based vision system is used. The developed controller, the Kinect-based vision system, and the HIL configuration are validated in the HIL simulation-based environment. The results confirm that the proposed HIL system can be an efficient tool for verifying the performance of the hardware and simulation designs of flatness-based control systems for omnidirectional mobile robots.

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Intuitive dynamic modeling and flatness-based nonlinear control of a mobile robot

Cited by 19 publications

References 33 publications

A multiple sensor fusion based drift compensation algorithm for mecanum wheeled mobile robots

A multiple sensor fusion based drift compensation algorithm for mecanum wheeled mobile robots

4-mecanum wheeled mobile robot actuator fault detection & isolation using unknown input observer-based approach

Flatness-based control scheme for hardware-in-the-loop simulations of omnidirectional mobile robot

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