From May 12 to 14, 2023, the 12th IEEE Conference on Data‑Driven Control and Learning Systems was successfully held at Panlong Villa Hotel, Xiangtan City, Hunan Province. The event was co‑hosted by the Technical Committee on Data‑Driven Control, Learning and Optimization of Chinese Association of Automation and Qingdao University, undertaken by the School of Information and Electrical Engineering of Hunan University of Science and Technology, and co‑organized by IEEE Beijing Section and Beijing Information Science and Technology University. The conference featured keynote speeches, special workshops, pre‑conference tutorials, parallel sessions and poster presentations. As the exclusive sponsor of this conference, CHINGMU was honoured to participate. On‑site demonstrations of ground‑air cooperation and UAV positioning‑tracking were carried out with CHINGMU’s self‑developed optical motion‑capture system, introducing its applications in scientific research and automation to the attendees.

△ Highlights from DDCLS

CHINGMU’s robust underlying‑technology strength drew extensive attention and inquiries from numerous research professors.

△ Photo: Zhang Haiwei, General Manager of CHINGMU, introduces products to visiting scholars

CHINGMU’s self‑developed MC‑series optical motion‑capture system boasts six prominent advantages: high precision, low latency, dead‑zone‑free coverage, compatibility with active‑light sources for wide‑ranging scenarios, large‑scale multi‑target tracking, and rich interfaces supporting secondary development.

The UAV‑oriented MC optical motion‑capture system supports both active‑light and passive‑light tracking. Adaptable to various complex environments, it is widely applied in trajectory positioning, cooperative control, autonomous obstacle avoidance, target following and other research fields.

Optical motion‑capture systems will serve as a vital technological carrier for future advances in scientific research and industrial automation. CHINGMU is proud to take part in this technological transformation and contribute to research‑oriented and automation‑related industries.