Target tracking technology is a key research area in the field of mobile robots, with wide applications in logistics, security, autonomous driving, and more. It generally involves two main components: target recognition and target following. However, the limited computational power of the mobile robot’s controller makes achieving high precision and fast target recognition and tracking a challenge. To address the challenges posed by limited computing power, this paper proposes a target-tracking control algorithm based on lightweight neural networks. First, a depthwise separable convolution-based backbone is introduced for feature extraction. Then, an efficient channel attention module is incorporated into the target recognition algorithm to minimize the impact of redundant features and emphasize important channels, thereby reducing model complexity and enhancing network efficiency. Finally, based on the data collected from visual and ultrasonic sensors, a model predictive control strategy is used to achieve target tracking. Validation of the proposed algorithm is conducted using a mobile robot equipped with Raspberry Pi 4B. Experimental results demonstrate that the proposed algorithm achieves rapid target tracking.

With over 50 years of active research in Nigeria, Astronomy is still faced with various challenges, in particular poor funding from government and the prevailing harsh economic condition. Despite these challenges, there is a recent growing interest of the younger generation in astronomy which comes mainly through astronomy outreach programme, biennial summer schools and annual conference of the astronomical society of Nigeria. Electric power supply has remained a long-lasting problem and contributes immensely, especially in rural communities, to the hindrance faced in areas of education like astronomy which can not progress without the use of computers for data visualisation and analysis. As a matter of fact, cultural astronomy already exist and is well recognised in these poor communities.

The amazing credit card size 5V DC battery-powered Raspberry Pi computers and Virtual Observatory(VO) will play a major role in doing modern astronomy in these communities despite these hindrances. We target the less privileged students in six rural secondary schools (located in 6 different states) by bringing to their doorsteps astronomy using low cost but effective tools. Various hands-on astronomy exercises were carried out with the VO tools. We discuss our experiences with the students and teachers with this pilot project which at the same time promotes not only astronomy but also Science Technology Engineering and Mathematics (STEM). We intend to expand the number of schools covered through grant from IAU and donations of the Raspberry Pi computers from astronomy enthusiasts and organisations.