Development of path tracking control of a tracked vehicle for an unmanned ground vehicle

2020 ◽  
Vol 8 (4) ◽  
pp. 136
Author(s):  
Muhammad Akhimullah Subari ◽  
Khisbullah Hudha ◽  
Zulkiffli Abd Kadir ◽  
Syed Mohd Fairuz Bin Syed Mohd Dardin ◽  
Noor Hafizah Amer
Author(s):  
Noor Hafizah Amer ◽  
Syed Mohd Fairuz Bin Syed Mohd Dardin ◽  
Khisbullah Hudha ◽  
Zulkiffli Abd Kadir ◽  
Muhammad Akhimullah Subari

Author(s):  
Zaharuddeen Haruna ◽  
Muhammed B. Mu'azu ◽  
Yusuf S. Abubakar ◽  
Emmanuel A. Adedokun

2015 ◽  
Author(s):  
Can Wang ◽  
Bo Yang ◽  
Gangfeng Tan ◽  
YiRui Wang ◽  
Li Zhou

2022 ◽  
Vol 12 (1) ◽  
pp. 525
Author(s):  
Yasuhiro Fukuoka ◽  
Kazuyuki Oshino ◽  
Ahmad Najmuddin Ibrahim

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position.


2020 ◽  
Vol 53 (3-4) ◽  
pp. 501-518
Author(s):  
Chaofang Hu ◽  
Lingxue Zhao ◽  
Lei Cao ◽  
Patrick Tjan ◽  
Na Wang

In this paper, a strategy based on model predictive control consisting of path planning and path tracking is designed for obstacle avoidance steering control problem of the unmanned ground vehicle. The path planning controller can reconfigure a new obstacle avoidance reference path, where the constraint of the front-wheel-steering angle is transformed to formulate lateral acceleration constraint. The path tracking controller is designed to realize the accurate and fast following of the reconfigured path, and the control variable of tracking controller is steering angle. In this work, obstacles are divided into two categories: static and dynamic. When the decision-making system of the unmanned ground vehicle determines the existence of static obstacles, the obstacle avoidance path will be generated online by an optimal path reconfiguration based on direct collocation method. In the case of dynamic obstacles, receding horizon control is used for real-time path optimization. To decrease online computation burden and realize fast path tracking, the tracking controller is developed using the continuous-time model predictive control algorithm, where the extended state observer is combined to estimate the lumped disturbances for strengthening the robustness of the controller. Finally, simulations show the effectiveness of the proposed approach in comparison with nonlinear model predictive control, and the CarSim simulation is presented to further prove the feasibility of the proposed method.


Author(s):  
Peng Hang ◽  
Xinbo Chen

In this study, a novel 4-wheel-steering electric vehicle is proposed as an autonomous ground vehicle. It aims to study the path tracking control algorithm of the 4-wheel-steering autonomous ground vehicle for intelligent driving.. Path tracking model is built for path tracking controller design based on a single track model. Besides, the linear parameter-varying system model is constructed to make the path tracking controller adaptive to different longitudinal velocities and road friction coefficients. Furthermore, a linear quadratic regulator controller for path tracking is designed and stability analysis is carried out. To eliminate the error caused by disturbance, feedforward control is combined with a linear quadratic regulator controller. To verify the path tracking performance of the designed controller, numerical simulations are carried out based on a high-fidelity and full-vehicle model constructed in CarSim. Moreover, real road experiments are performed. Both the simulation results and experiment results show that the designed controller has good path tracking performance. In addition, the path tracking controller shows good robustness to deal with different longitudinal velocities and road friction coefficients.


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