Skid Steering based Driving Control of a Robotic Vehicle with Six In-Wheel Drives

Kang, Juyong; Kim, Wongun; Yi, Kyongsu; Jung, Soungyong; Lee, Jong-Seok

doi:10.4271/2010-01-0087

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…A dynamic model is developed of 4WD-SSWMR for 2D motion (Wang et al , 2015). In another study, a dynamic model for 6WD-SSWMR with articulated suspension is proposed (Kang et al , 2010b). A model for SSWMR with six in-wheel motors using Truck Sim is used for designing a control algorithm based on optimum tire force distribution (Kim et al , 2015).…”

Section: Modeling Of Skid-steer Wheeled Mobile Robotsmentioning

confidence: 99%

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Khan

Malik

Raza

et al. 2020

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Purpose The purpose of this paper is to provide a comprehensive and unified presentation of recent developments in skid-steer wheeled mobile robots (SSWMR) with regard to its control, guidance and navigation for the researchers who wish to study in this field. Design/methodology/approach Most of the contemporary unmanned ground robot’s locomotion is based upon the wheels. For wheeled mobile robots (WMRs), one of the prominent and widely used driving schemes is skid steering. Because of mechanical simplicity and high maneuverability particularly in outdoor applications, SSWMR has an advantage over its counterparts. Different prospects of SSWMR have been discussed including its design, application, locomotion, control, navigation and guidance. The challenges pertaining to SSWMR have been pointed out in detail, which will seek the attention of the readers, who are interested to explore this area. Findings Relying on the recent literature on SSWMR, research gaps are identified that should be analyzed for the development of autonomous skid-steer wheeled robots. Originality/value An attempt to present a comprehensive review of recent advancements in the field of WMRs and providing references to the most intriguing studies.

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Section: Modeling Of Skid-steer Wheeled Mobile Robotsmentioning

confidence: 99%

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Khan

Malik

Raza

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The geometric and kinematic links between wheel slippage, the path following control and linear controllers employing robot localization coordinates are presented in [7] and [8,9]. For accurate vehicle velocity prediction, a dynamic model with actuator saturation and power constraints is proposed in [10] and [11]. In [12] and [13], a nonholonomic mobile robot's kinematic and torque controllers are integrated.…”

Section: Introductionmentioning

confidence: 99%

Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Pandiaraj¹,

Muralidharan²

2023

Intelligent Automation &Amp; Soft Computing

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Four-wheeled, individual-driven, nonholonomic structured mobile robots are widely used in industries for automated work, inspection and exploration purposes. The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure. The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots. However, there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis's motion. As a result, the mobile robot has limited performance, such as chattering during curved movement. In this research work, a three-tiered adaptive robust control with fuzzy parameter estimation, including dynamic modeling, direct torque control and wheel slip control is proposed. Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller (ARC) parameters and tracking the trajectories with less tracking error as well as high tracking accuracy. This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique. Our suggested approach outperforms the existing control methods such as Fuzzy, proportional-integral-derivative (PID) and adaptive robust controller with discrete projection (ARC-DP). The experimental results show that the scheduled performance index decreases by 2.77% and 4.76%. All the experimental simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.

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“…Kim et al 13 used an adaptive proportional–derivative (PD) control to generate the yaw moment, and the optimal torque distribution is formulated as the solution of a parametric optimization problem. Kang and colleagues 14–16 and Yan et al 17 created a cost function considering the friction circle through the estimation of longitudinal and vertical tire force. As Faurous and Vaslin 18 modeled the skid-steering vehicle with emphasis on the ground contact force with wheels and concluded that the normal force distribution of the vehicle is efficient to increase the steering performance, Zhao et al 19 considered the vertical load dynamics to reduce the vertical load transfer.…”

Section: Introductionmentioning

confidence: 99%

Speed-adaptive motion control algorithm for differential steering vehicle

Chen

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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The differential steering vehicle uses the in-wheel motors to drive the wheels directly and individually. However, in order to deliver the required structural robustness, the differential steering vehicle discarded the mechanical steering system and achieved vehicle steering by applying differential speed between the left and right wheels. This paper presents a novel speed-adaptive motion control algorithm based on the unique chassis configuration to enhance the performance in vehicle handling and lateral stability. The proposed control method first estimates the driver’s driving intention, from which reference wheel speeds are individually generated for each wheel based on their respective slipping and skidding status. Finally, the torque command is automatically adjusted by the speed-tracking controller by proactive adaptation of the wheel spinning resistance to effectively avoid excessive slip on low friction. This method exploits the fact that the torque at the steady state will always be equal to the available longitudinal force, thereby delivering the sophisticated tire force estimation without additional computational efforts, and ultimately helping conserve energy and promote lateral stability. The essential road information collected by this algorithm is also made available to drivers for improved vehicle controllability. The algorithm is subjected to three experimental case scenarios—pivot steering, low-friction driving, and curvilinear driving—through TruckSim–Simulink co-simulations and real vehicle tests, and the results have validated the algorithm in realizing the high-performance steering and maneuvering capabilities for six-wheeled differential steering vehicles.

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Skid Steering based Driving Control of a Robotic Vehicle with Six In-Wheel Drives

Cited by 5 publications

References 10 publications

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Speed-adaptive motion control algorithm for differential steering vehicle

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