Highly Accurate Robot Calibration Using Adaptive and Momental Bound with Decoupled Weight Decay
<|reference_start|>Highly Accurate Robot Calibration Using Adaptive and Momental Bound with Decoupled Weight Decay: Within the context of intelligent manufacturing, industrial robots have a pivotal function. Nonetheless, extended operational periods cause a decline in their absolute positioning accuracy, preventing them from meeting high precision. To address this issue, this paper presents a novel robot algorithm that combines an adaptive and momental bound algorithm with decoupled weight decay (AdaModW), which has three-fold ideas: a) adopting an adaptive moment estimation (Adam) algorithm to achieve a high convergence rate, b) introducing a hyperparameter into the Adam algorithm to define the length of memory, effectively addressing the issue of the abnormal learning rate, and c) interpolating a weight decay coefficient to improve its generalization. Numerous experiments on an HRS-JR680 industrial robot show that the presented algorithm significantly outperforms state-of-the-art algorithms in robot calibration performance. Thus, in light of its reliability, this algorithm provides an efficient way to address robot calibration concerns.<|reference_end|>
@article{chen2024highly,
    title={Highly Accurate Robot Calibration Using Adaptive and Momental Bound with
  Decoupled Weight Decay},
    author={Tinghui Chen, Shuai Li},
    journal={arXiv preprint arXiv:2408.12087},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.12087},
    primaryClass={cs.RO}
}