Trajectory tracking control of a nonholonomic mobile robot with differential drive

Sousa, Rigoberto Luis Silva; Forte, Marcus Davi do Nascimento; Nogueira, Fabrício G.; Torrico, Bismark C.

doi:10.1109/argencon.2016.7585356

Cited by 16 publications

(8 citation statements)

References 4 publications

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“…However, it is desirable to describe most control configurations according the wheel angular velocities (

). The general kinematic model of DDMR is defined as [ 37 , 38 , 39 , 40 , 41 , 42 ],

…”

Section: Mathematical Modelling Of the Differential Drive Mobile Robotmentioning

confidence: 99%

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A New Nonlinear Dynamic Speed Controller for a Differential Drive Mobile Robot

Hameed

Abbud

Abdulsaheb³

et al. 2023

Entropy

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A disturbance/uncertainty estimation and disturbance rejection technique are proposed in this work and verified on a ground two-wheel differential drive mobile robot (DDMR) in the presence of a mismatched disturbance. The offered scheme is the an improved active disturbance rejection control (IADRC) approach-based enhanced dynamic speed controller. To efficiently eliminate the effect produced by the system uncertainties and external torque disturbance on both wheels, the IADRC is adopted, whereby all the torque disturbances and DDMR parameter uncertainties are conglomerated altogether and considered a generalized disturbance. This generalized disturbance is observed and cancelled by a novel nonlinear sliding mode extended state observer (NSMESO) in real-time. Through numerical simulations, various performance indices are measured, with a reduction of 86% and 97% in the ITAE index for the right and left wheels, respectively. Finally, these indices validate the efficacy of the proposed dynamic speed controller by almost damping the chattering phenomena and supplying a high insusceptibility in the closed-loop system against torque disturbance.

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“…However, it is desirable to describe most control configurations according the wheel angular velocities (

). The general kinematic model of DDMR is defined as [ 37 , 38 , 39 , 40 , 41 , 42 ],

…”

Section: Mathematical Modelling Of the Differential Drive Mobile Robotmentioning

confidence: 99%

“…Linear velocity is computed by averaging the linear velocities of the two wheels in the LCS [ 37 , 38 , 39 , 40 ],

…”

Section: Mathematical Modelling Of the Differential Drive Mobile Robotmentioning

confidence: 99%

A New Nonlinear Dynamic Speed Controller for a Differential Drive Mobile Robot

Hameed

Abbud

Abdulsaheb³

et al. 2023

Entropy

View full text Add to dashboard Cite

show abstract

“…The kinematic model equations depend on the geometrical structure of the DDWMR [3]. However, most of the 3-wheel DDWMRs have the same kinematic equation which is constructed as follows [3], [5], [12], [13], [15]:…”

Section: ) Kinematic Modelmentioning

confidence: 99%

“…The DDWMR has some different forms, such as a 2wheel, a 3-wheel, or a 4-wheel type. We can find the 2-wheel type in [13], the 3-wheel type in [5], [7], [10], [11], [18], [19], [20], [23], and the 4-wheel type in [15], [17]. The 3wheel type is the most popular form which comprises of two fixed powered wheels mounted on both left and right side of the robot platform and one passive castor wheel used for balance and stability.…”

Section: Introductionmentioning

confidence: 99%

Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot

et al. 2020

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In order to select the best controller for a Differential Drive Wheeled Mobile Robot (DDWMR), an energy consumption comparison relating to tracking accuracy is used as a very strict criterion. Therefore, this paper reviews some well-known controllers designed for the DDWMR. Furthermore, there are presented several experiments with the extensible open-source code programmed in Python. Such an extensible open-source code presentation could serve as a tool for simulating, comparing, and evaluating a set of different control algorithms. The kinematic and dynamic models of the DDWMR and control algorithms are implemented in this open-source code to determine a travel time, a distance between the robot's position and a given path, a linear velocity, an angular velocity, a travel path length, and a total kinetic energy loss of the DDWMR. These simulation results are used to compare and evaluate the given control algorithms. Moreover, the simulation results also enable to answer the question of whether a significant increase in energy consumption is worth shortening the travel path by just a bit. Finally, this paper includes a direct link to the stored experiments which are runnable and could serve as a proof. Besides, users can also easily supplement with other controllers and different paths to evaluate robot tracking control algorithms.

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“…Controlling mobile robots can be done using model-based control or non-model based such as AI [12]- [15]. A model-based robot is an excellent approach to control a robot because it is easier to analyze its stability [16], [17]. However, it is hard to formulate the mathematical model representing all physical forces acting on the robot [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Path Tracking and Position Control of Nonholonomic Differential Drive Wheeled Mobile Robot

Auzan

Hujja

Fuadin

et al. 2021

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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Differential drive wheeled mobile robot (DDWMR) is one example of a robot with a constrained movement, Multiple Input Multiple Output (MIMO), and nonlinear system. Designing a low resource position and heading controller using linear MIMO methods such as LQR became a problem because of the linearization of robot dynamics at zero value. One of the solutions is to design a MIMO controller using a Single Input Single Output (SISO) controller. This work design a controller using PID for DDWMR Jetbot and selects the best feedback gain using different scenarios. The designed controller manipulates both motors by using calculated control signal to achieve a complex task such as path tracking with robot position in x-Axis, y-Axis, and heading angle as the feedback. The priority between position and heading angle can be adjusted by changing three feedback gains. The controller was tested, and the best gain was selected using Integral Absolute Error (IAE) metrics in a path tracking task with four different path shapes. The proposed methods can track square, circle, and two types of infinity shape paths, with the less well-formed shape being the four edges square path.

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Trajectory tracking control of a nonholonomic mobile robot with differential drive

Cited by 16 publications

References 4 publications

A New Nonlinear Dynamic Speed Controller for a Differential Drive Mobile Robot

A New Nonlinear Dynamic Speed Controller for a Differential Drive Mobile Robot

Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot

Path Tracking and Position Control of Nonholonomic Differential Drive Wheeled Mobile Robot

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