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Mihai Crengani?, Radu-Eugen Breaz, Sever-Gabriel Racz, Claudia-Emilia Gîrjob, Cristina-Maria Biri?, Adrian Maro?an and Alexandru Bârsan
This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying ...
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Haojun Wen, Xiaodong Ma, Chenjian Qin, Hao Chen and Huanyu Kang
The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used...
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Hui Liu, Kun Li, Luyao Ma and Zhijun Meng
Headland boundary identification and ranging are the key supporting technologies for the automatic driving of intelligent agricultural machinery, and they are also the basis for controlling operational behaviors such as autonomous turning and machine lif...
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Chan-Hoo Kim, Ji-Hyun Choi and Sung-Young Park
Contaminated autonomous-driving sensors frequently malfunction, resulting in accidents; these sensors need regular cleaning. The autonomous-driving sensor-cleaning nozzle currently used is the windshield-washer nozzle; few studies have focused on the sen...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Bohdan Petryshyn, Serhii Postupaiev, Soufiane Ben Bari and Armantas Ostreika
The development of autonomous driving models through reinforcement learning has gained significant traction. However, developing obstacle avoidance systems remains a challenge. Specifically, optimising path completion times while navigating obstacles is ...
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Inês A. Ribeiro, Tiago Ribeiro, Gil Lopes and A. Fernando Ribeiro
This paper presents a solution for an autonomously driven vehicle (a robotic car) based on artificial intelligence using a supervised learning method. A scaled-down robotic car containing only one camera as a sensor was developed to participate in the Ro...
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Zhuangzhuang Yang, Chengxin Pang and Xinhua Zeng
Predicting the future trajectories of multiple agents is essential for various applications in real life, such as surveillance systems, autonomous driving, and social robots. The trajectory prediction task is influenced by many factors, including individ...
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Yanfeng Li, Hsin Guan, Xin Jia and Chunguang Duan
A scenario vehicle in autonomous driving simulations is a dynamic entity that is expected to perform trustworthy bidirectional interaction tasks with the autonomous vehicle under test. Modeling interactive behavior can not only facilitate better predicti...
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Fei Lai and Xiaoyu Wang
A pre-emptive braking control method is proposed to improve the stability of autonomous vehicles during emergency collision avoidance, aiming to imitate the realistic human driving experience. A linear model predictive control is used to derive the front...
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