A versatile humanoid robot platform for dexterous manipulation and human-robot collaboration

Humanoid robots have attracted much attention by virtue of their compatibility with human environments. However, biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in the current state. Hence, rationally combining a humanoid robot with different stable mobile platforms is a favoured solution for diverse scenarios. Here, a new versatile humanoid robot platform, aiming to provide a generic solution that can be flexibly deployed in diverse scenarios, for example, indoors and fields is presented. Versatile humanoid robot platform incorporates multimodal perception, and extensible interfaces on hardware and software, allowing it to be rapidly integrated with different mobile platforms and end-effectors, only through easy-to-assemble interfaces. Additionally, the platform has achieved impressive integration, lightness, dexterity, and strength in its class, with human-like size and rich perception, targeted to have human-intelligent manipulation skills for human-engineered environments. Overall, this article elaborates on the reasoning behind the design choices, and outlines each subsystem. Lastly, the essential performance of the platform is successfully demonstrated in a set of experiments with precise and dexterous manipulation, and human-robot collaboration requirements.

Automated summary

Humanoid robots have attracted attention for their compatibility with human environments, but they still lack stability and reliability in real-world settings. Combining humanoid robots with various stable mobile platforms is a favored solution. This article presents a versatile humanoid robot platform, which allows flexible deployment in diverse scenarios by incorporating multimodal perception and extensible interfaces. The platform has achieved impressive integration, lightness, dexterity, and strength, with the goal of human-intelligent manipulation skills for human-engineered environments. The article elaborates on design choices, subsystems, and demonstrates the platform's performance through experiments.