JD.com announces plans to deploy 3 million robots and 1 million vehicles over five years to enhance logistics automation.
JD.com, a leading Chinese e-commerce firm, is set to enhance its logistics capabilities by introducing 3 million robots, 1 million autonomous vehicles, and 100,000 drones over the next five years. This ambitious initiative was unveiled at a recent event in Beijing, where the company introduced its Wolf Robot industrial series, aimed at automating repetitive tasks within its logistics network.
The robots will play a crucial role in various operations, including picking, sorting, transporting goods, and delivering orders with minimal human input. Some of the machines are designed to operate in extreme conditions, such as temperatures as low as -20 °C, and include specialized systems for medical deliveries.
Currently, JD.com employs approximately 700,000 individuals in logistics and delivery roles. As automation progresses, the company has pledged to not only reduce reliance on human labor but also transition some workers into technical positions focused on maintaining and repairing the new robotic systems.
Employee Retraining and Data Collection Initiatives
JD.com’s founder, Liu Qiangdong, has previously introduced the Nirvana Plan, which emphasizes retraining couriers and warehouse staff to collaborate with robots. This plan aims to preserve jobs by shifting employees into roles that involve technical maintenance of robotic systems.
In tandem with its equipment expansion, JD.com is prioritizing data collection, intending to accumulate over 10 million hours of operational data from both robots and humans. This data will be instrumental in refining artificial intelligence systems that interact with the physical environment.
To support these initiatives, JD.com is establishing more than 80 RoboBase centers across China for robotics research and development. These centers will focus on pilot production, data annotation, and equipment maintenance. Furthermore, the company has partnered with chip manufacturer Moore Threads to develop a computing cluster utilizing 100,000 domestically produced chips, aimed at enhancing AI training and deployment.
Analysts note that the current global dataset on robot-environment interactions is limited, with around 500,000 hours available, and estimate that tens of millions of hours will be required to train comprehensive AI models for robotics.
