Intelligent pose detection of bipedal humanoid robots
The intelligent pose detection of bipedal humanoid robots represents a pivotal research direction within the realm of robotics technology,encompassing the interdisciplinary fusion of computer vision,machine learning,and robotic control.As bipedal humanoid robots gain significant applications in domains such as household services,emergency medical rescue,and efficient industrial production,there arises a heightened demand for enhanced pose detection capabilities.However,the prevailing pose detection algorithms are predominantly focused on human pose analysis,and their direct application to bipedal humanoid robots often falls short of achieving desired outcomes.Consequently,there is a necessity to devise tailored algorithms that cater to the unique anthropomorphic form of bipedal humanoid robots,thereby elevating their pose detection proficiency.This paper presents an intelligent pose detection method for bipedal humanoid robots.By meticulously examining the theoretical foundations and implementation mechanisms of existing human pose detection algorithms,and integrating a channel-based attention mechanism,this paper has effectively bolstered the detection accuracy and robustness of the proposed model.
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