ISE student won the best paper award at the 3rd International Conference on Intelligent Computing, Communication and Devices

ISE student Miss. CAI Jiaxiao have received the best paper award at the International Conference on Intelligent Computing, Communication and Devices 2017 for the paper “Higher Individuality for Effective Swarm Intelligence”. This research paper presents a glimpse of the results from the research they have conducted for the final year project which Miss. CAI Jiaxiao completed under the supervision of Dr. Velvet Chen at the Department of Industrial and Systems Engineering early this year.

The Conference Best Paper Award is presented to Miss. CAI Jiaxiao and her supervisor Dr. Velvet Chen (ISE) for their paper titled, “Higher Individuality for Effective Swarm Intelligence”, and it is highly competitive, with two rounds of selection processes to screen out the top three papers among more than 50 conference papers. The Best Paper Award recognizes their exceptional research merit and industrial impact dealing with a subject related to intelligence computing, communication and devices.

The International Conference on Intelligent Computing, Communication & Devices 2017 (ICCD-2017) is held during December 9-10, 2017 in Shenzhen, China. This conference gathered academicians, researchers, scientists and professionals from around the globe to share their knowledge and expertise in the field of intelligent computing, communication and devices. The selected paper of the International Conference on Intelligent Computing, Communication and Devices 2017 (ICCD-2017) will be published in Advances in Intelligent Systems and Computing (ISSN: 2194-5357) by Springer-Verlag.

The research paper explores way in which robotic swarm system can be developed to be more efficient and flexible with the aid of a novel concept, called swarm individuality. Note the expanding demands of robotic tasks with higher complexity, higher dimensionality, and different information density, other than employing the conventional low cost–effective approach of increasing the number of swarm, this paper intends to adopt higher swarm individuality to design a swarm system with higher flexibility and re-configurability. The proposed swarm system is realized by a target following technique using computer vision and a novel path planning algorithm, directional A* algorithm. With an aim to explore the possibility to apply swarm robot in service sector, the system has been tested with a self–developed swarm robot target following system, the Auto–Cart (a new supermarket service system). It is believed that the proposed swarm system could also be implemented into various sectors such as exploration, rescue, military and agriculture.