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Fan Yang - IEEE Xplore Author Profile

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A primary challenge in robotic tool use is achieving precise manipulation with dexterous robotic hands to mimic human actions. It requires understanding human tool use and allocating specific functions to each robotic finger for fine control. Existing work has primarily focused on the overall grasping capabilities of robotic hands, often neglecting the functional allocation among individual finger...Show More
Transformer-based approaches have demonstrated outstanding performance in monocular 3-D object detection, which involves predicting 3-D attributes from a single 2-D image. These transformer-based methods typically rely on visual and depth representations to identify crucial queries related to objects. However, the feature and location of queries are expected to learn adaptively without any prior k...Show More
Transformer-based methods have demonstrated superior performance for monocular 3D object detection recently, which aims at predicting 3D attributes from a single 2D image. Most existing transformer-based methods leverage both visual and depth representations to explore valuable query points on objects, and the quality of the learned query points has a great impact on detection accuracy. Unfortunat...Show More
This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation...Show More