Year: 2025
Type: article
Abstract: With the in-depth development of digital twin technology in modern agriculture, smart pig farm construction is evolving from basic environmental modeling toward refined, bio-behavior-driven approaches. This study addresses the non-standard body configurations and complex behavioral patterns of pig models by proposing a binding method that combines lightweight skeletal design with automated weight allocation strategies. The method optimizes skeletal layout schemes based on pig physiological structures and behavioral patterns, replacing manual painting processes through geometry-driven weight calculation strategies to achieve a balance between efficiency and animation naturalness. The research constructs a motion template library containing common behaviors such as walking and foraging, conducting quantitative testing and comprehensive evaluation in simulation systems. Experimental results demonstrate that the proposed method achieves significant improvements: it demonstrated superior computational efficiency with 95.2% reduction in computation time, memory storage space reduced by 91.7% through weight matrix sparsification (density controlled at 8.3%), and weight smoothness was maintained at 0.955 while cross-region weight leakage reduced from 15.3% to 2.1%. The method effectively supports animation expression of eight typical pig behavioral patterns with key joint angle errors controlled within 2.3 degrees, providing a technically viable and economically feasible pathway for virtual modeling and intelligent interaction in smart agriculture.
Source: Applied Sciences
DOI: 10.3390/app16010019
Authors: Jun Yang, Bo Liu
Institution: Hunan Agricultural University
Language: English
Topic: Human Motion and Animation
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: 互联网医疗中的关键图像增强技术研究
OpenAlex ID: W7116060000
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