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traditional service robots face many challenges. for example, in catering scenarios, the service robot's serving link after delivering meals has not been opened up, and human intervention is still required; in hotel scenarios, robots can complete welcoming and room delivery, but room cleaning and room service still rely on manual labor, etc. these problems make it impossible to complete the service closed loop, affecting the customer's experience. however, pudu d7 breaks these limitations. the gripper or dexterous hand it is equipped with can press, pick, take, and put freely and flexibly, and complete tasks such as elevator button operation, access card swiping, and serving dishes by operating the robotic arm. this versatility not only simplifies the service process, but also more effectively realizes end-to-end intelligence.
the success of pudu d7 is closely related to the embodied learning ability of the "scaling law". it can self-optimize and learn based on environmental information and user needs to achieve more complex tasks. at the same time, the robot based on the service manipulator solves the problem of task generalization. this cross-scenario application allows pudu d7 to not only complete the service process in the catering scenario, but also complete multiple tasks such as welcoming guests, luggage handling, and room service in hotel management, and complete loading and unloading, sorting, handling, and outbound delivery in industrial production.
under the leadership of purdue robotics, humanoid robots will empower multiple sub-industries such as catering, retail, hotels, industry, medical care, education, elderly care, and public services. general-purpose embodied service robots will usher in a new era of rapid commercialization.
the success of pudu d7 also highlights the development trend of service robots: from single-scenario to multi-scenario applications, from simple tasks to complex collaboration, service robots are moving towards a more intelligent and efficient direction.
