This paper aims to design an unmanned trolley target search and adaptive charging system based on multimodal perception, so as to improve the autonomous navigation, target positioning and search ability of unmanned trolley in complex environment, and realize the autonomous management and supplement of energy. The paper first summarizes the principle of multimodal perception technology and its application in unmanned car, including various data fusion methods, such as vision, radar and acoustics. Subsequently, the target search system of the unmanned car is designed, through the feature extraction, identification algorithm and path planning strategy, to realize the efficient search and positioning of the target. At the same time, an adaptive charging system is built, which realizes the autonomous charging function of unmanned cars through energy state monitoring, identification and positioning of charging facilities, and the strategy of autonomous navigation and charging docking. In the experimental verification stage, this paper builds the hardware platform of unmanned car and designs the corresponding software system. The effectiveness and reliability of target search and adaptive charging system are verified through the indoor and outdoor environment. The experimental results show that the system can accurately identify the target, plan the reasonable path, and independently find the charging facility for charging when the energy is insufficient. This study not only enriches the research results in the field of unmanned vehicle technology, but also provides strong support for the application of unmanned vehicle in a complex environment. In the future, it will further optimize the system performance, expand the application field, and promote the sustainable development of unmanned car technology.

Weihua Shang. Design of Unmanned Trolley Target Search and Adaptive Charging System Based on Multimodal Perception. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 3: 110-115. https://doi.org/10.25236/AJETS.2024.070316.

[1] Huang Xinpeng, Cai Qingzhong, Yang Gongliu, et al. Indoor navigation and positioning method based on UWB. School of Intelligent Science, National University of Defense Technology, 2023:8.

[2] Jin Mengfan. Research and realization of vision enhancement technology for intelligent trolley in complex environment. Beijing University of Posts and Telecommunications, 2022.

[3] Chen Gaoyuan. Research on the algorithm of obstacle avoidance and path optimization for unmanned trolley. Civil Aviation University of China, 2021.

[4] Lin Yuankai. Research on intelligent subject of intelligent method based on parallel fusion and modal information. Shenzhen University, 2019.

[5] Yang Zhigang. Research on vehicle operation and safety intelligence perception methods based on multimodal information fusion and adaptive evolutionary neural network. Shenzhen University, 2019.

[6] Shang Mingchao. Research and implementation of indoor positioning algorithm of unmanned car based on QR code and corner point label. Southwest Jiaotong University, 2017.

[7] Weixi Wang, Xiaoming Li, Linfu Xie, Haibin Lv, and Zhihan Lv. Unmanned Aircraft System Airspace Structure and Safety Measures Based on Spatial Digital Twins. IEEE Transactions on Intelligent Transportation Systems, 2021.