Coordinated path tracking of two vision-guided tractors for heavy-duty robotic vehicles

Wu, Xing; Zhang, Ying; Zou, Ting; Zhao, Long; Lou, Peihuang; Yin, Zuyu

doi:10.1016/j.rcim.2018.03.012

Cited by 25 publications

(8 citation statements)

References 19 publications

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“…In another study by [24] a robot tower-crane system was developed by studying the feasibility of a laser-technology-based lifting-path tracking system to improve productivity by 9.9%-50%. A path tracking was developed by Huang et al in [25] for two vision-guided tractors of a robotic vehicle to make the two robotic vehicles move along a guide path accurately and smoothly.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

Batayneh

Aburmaileh

2020

Sensors

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The last decade observed a significant research effort directed towards maneuverability and safety of mobile robots such as smart wheelchairs. The conventional electric wheelchair can be equipped with motorized omnidirectional wheels and several sensors serving as inputs for the controller to achieve smooth, safe, and reliable maneuverability. This work uses the decentralized algorithm to control the motion of omnidirectional wheelchairs. In the body frame of the omnidirectional wheeled wheelchair there are three separated independent components of motion including rotational motion, horizontal motion, and vertical motion, which can be controlled separately. So, each component can have its different sub-controller with a minimum tracking error. The present work aims to enhance the mobility of wheelchair users by utilizing an application to control the motion of their attained/unattained smart wheelchairs, especially in narrow places and at hard detours such as 90˚ corners and U-turns, which improves the quality of life of disabled users by facilitating their wheelchairs’ maneuverability. Two approaches of artificial intelligent-based controllers (PD-Fuzzy-P and GA-PID controllers) are designed to optimally enhance the maneuverability of the system. MATLAB software is used to simulate the system and calculate the Mean Error (ME) and Mean Square Error (MSE) for various scenarios in both approaches, the results showed that the PD-Fuzzy-P controller has a faster convergence in trajectory tracking than the GA-PID controller. Therefore, the proposed system can find its application in many areas including transporting locomotor-based disabled individuals and geriatric people as well as automated guided vehicles.

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Section: Introductionmentioning

confidence: 99%

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

Batayneh

Aburmaileh

2020

Sensors

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“…The controller design mainly falls into two categories: simple controller based only on the kinematics model; and integration of the former via robot dynamics. Kinematics models usually lead to velocity-driven, first-order differential equations [2], [5], [11], [12]. Sometimes these models are turned into geometric equations based on the instantaneous centre of curvature or trajectory approximation at each sampling instant [7], [15].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning With Lamé-Curve Blending for Motor-Saturation Avoidance Upon Mobile-Robot Turning

Ángeles²,

Zou

et al. 2020

IEEE Access

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In order to avoid motor saturation in turning maneuvers, an iterative Lamé-trajectory planning scheme is proposed to generate a smooth curvature-bounded transition trajectory for a differential-driving wheeled mobile robot (DWMR) switching from one straight path to another. The scheme consists of Lamécurve blending, inverse-kinematics computation, peak-torque positioning and torque-saturation avoidance. Firstly, a Lamé-curve blending procedure based on affine transformations, is formulated to generate a smooth G 2-continuous transition trajectory for connecting two straight paths. Secondly, the platform twist is calculated according to the curvature of the Lamé-curve trajectory, then transformed into the actuated-joint rates by means of the inverse-kinematics model. Thirdly, a peak-torque positioning technique is developed to estimate the peak torques of the driving wheels when the DWMR tracks the trajectory, by combining the computed-torque method and the inverse-dynamics model. Finally, an iterative r-step saturation-avoidance prediction planning strategy is devised to suppress the peak motor torques, by means of two torque limitation schemes via adjusting trajectory curvature and robot speed. The simulation results show that, compared with the conventional planning techniques for circular arcs, our trajectory planning scheme can generate a smooth saturation-free transition trajectory with feasible curvature and traveling speed. The scheme is significantly beneficial for trajectory tracking under finite actuation torque in turning maneuvers, thereby preventing any possible path deviation caused by insufficient torque.

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“…Automated guided vehicles (AGV) are a typical industrial mobile robot used for repeating transportation tasks in factories for decades [1][2][3]. Applying computer vision to mobile robot Appl.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Path Recognition against Image Noises for Vision Guidance of Automated Guided Vehicles in a Complex Workspace

Sun

Zou

et al. 2019

Applied Sciences

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Applying computer vision to mobile robot navigation has been studied more than twodecades. The most challenging problems for a vision-based AGV running in a complex workspaceinvolve the non-uniform illumination, sight-line occlusion or stripe damage, which inevitably resultin incomplete or deformed path images as well as many fake artifacts. Neither the fixed thresholdmethods nor the iterative optimal threshold methods can obtain a suitable threshold for the pathimages acquired on all conditions. It is still an open question to estimate the model parameters ofguide paths accurately by distinguishing the actual path pixels from the under- or oversegmentationerror points. Hence, an intelligent path recognition approach based on KPCA–BPNNand IPSO–BTGWP is proposed here, in order to resist the interferences from the complexworkspace. Firstly, curvilinear paths were recognized from their straight counterparts by means of apath classifier based on KPCA–BPNN. Secondly, an approximation method based on BTGWP wasdeveloped for replacing the curve with a series of piecewise lines (a polyline path). Thirdly, a robustpath estimation method based on IPSO was proposed to figure out the path parameters from a set ofpath pixels surrounded by noise points. Experimental results showed that our approach caneffectively improve the accuracy and reliability of a low-cost vision-guidance system for AGVs in acomplex workspace.

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Coordinated path tracking of two vision-guided tractors for heavy-duty robotic vehicles

Cited by 25 publications

References 19 publications

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

Trajectory Planning With Lamé-Curve Blending for Motor-Saturation Avoidance Upon Mobile-Robot Turning

Intelligent Path Recognition against Image Noises for Vision Guidance of Automated Guided Vehicles in a Complex Workspace

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