HANGZHOU, China, Jan. 6, 2022 /PRNewswire/ -- DEEP Robotics exhibited its intelligent quadruped robot Jueying Lite2 with its partner Alisys at CES 2022, the tech industry's annual trade show held this year in Las Vegas on January 5-7, 2022, showcasing cutting-edge robotics technologies. Jueying Lite2, the second-generation dexterous intelligent robot dog created by DEEP Robotics for scientific research institutions, universities and technology enthusiasts, has greatly improved motion control capabilities and delivers a much enhanced intelligent interactive experience compared with its predecessors, stimulating innovation in the realm of quadruped devices.
Jueying Lite2 has been displayed during the exhibition by DEEP Robotics' 2022 CES partner Alisys. DEEP Robotics is an Asian pioneer in several robotic technologies, with particular attention paid to the motion control algorithms that guide quadruped robots, the development of relevant key components and systems as well as intelligent environmental perception, while Alisys is committed to enhancing the capabilities of robots through cloud software and technology solutions with a focus on cloud solutions, artificial intelligence (AI) and blockchain.
Jueying Lite2 demonstrates its advanced performance at its CES debut
Deep Robotics' proprietary Jueying series robots include Jueying Lite2, Jueying Mini, Jueying and Jueying X20. The name Jueying was selected to epitomize the famous horse in China's ancient Three Kingdoms period. The young technology firm's choice of such a historically important name is meant to show how the robots reflect Chinese cultural heritage.
Notably, Jueying has been featured on the cover of the authoritative journal Science Robotics. The series has been tested in multiple application scenarios, including security patrol, reconnaissance and surveillance as well as public rescue. In 2021, for the first time a single Jueying robot dog effectively patrolled a 25,000 square-meter electrical substation and a 500 kV cable tunnel.
SOURCE DEEP Robotics