PhysGuided-PPO: Physics-guided proximal policy optimization for energy-dissipative soft grasping.

Authors

Siyun Yang, You Zhong, Yuehang Liu, Miao Xue, Yin Zhang, Wei Pu

Published in

ISA transactions. Sep 08, 2026. Epub Sep 08, 2026.

Abstract

Dynamic soft grasping involves short-duration impacts, rapid energy transfer, and transient contact-pressure peaks that are difficult to regulate using simplified controllers or data-driven exploration alone. This paper proposes PhysGuided-PPO, a lightweight physics-guided extension of proximal policy optimization for energy-dissipative pneumatic soft grasping. An offline-trained one-step predictor estimates the immediate impact response of candidate valve commands and uses these predictions to bias the Bernoulli logit of the on-off valve and the Gaussian mean of the proportional valve during action sampling. Simulations over 0.18-0.50 m/s impacts show that PhysGuided-PPO increases energy dissipation from 91.2% and 93.4% to 96.8%, while reducing peak contact pressure from 2.46 and 2.32 N/cm² to 2.17 N/cm². These results indicate that short-horizon predictive guidance can improve impact-aware valve control while retaining the on-policy PPO training structure.

PMID:
42731974
Bibliographic data and abstract were imported from PubMed on 13 Sep 2026.

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