Comparing Tactile Feedback Control and Grasp Stability in Warehouse Picking Robots

Emily D. Reyes

Authors

Emily D. Reyes Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida, USA Author

Keywords:

Tactile Feedback, Grasp Stability, Network Simulation, Warehouse Robotics, Latency

Abstract

The rapid expansion of global e-commerce has necessitated the deployment of highly automated warehouse systems, wherein robotic picking mechanisms play a central role. Traditional warehouse robots rely predominantly on computer vision for object localization and grasping; however, vision alone is often insufficient for handling fragile, deformable, or densely packed items where precise force regulation is required. Tactile feedback control offers a solution by enabling real-time slip detection and force adjustment, significantly enhancing grasp stability. As warehouse environments increasingly adopt decentralized, network-based control architectures such as edge computing and industrial internet of things platforms, the transmission of high-frequency tactile data over wireless networks introduces latency, jitter, and packet loss. This paper presents a comprehensive network simulation study investigating the impact of network performance on tactile feedback control and the resulting grasp stability of warehouse picking robots. By modeling a closed-loop haptic feedback system over various simulated network topologies, this research evaluates how different communication delays degrade grasping performance. The methodology integrates robotic simulation environments with network simulation tools to create a realistic testing framework for dynamic grasping tasks. The findings reveal critical latency thresholds beyond which grasp stability deteriorates exponentially, leading to object slippage or structural damage to fragile items. The study provides actionable insights for the design of industrial wireless networks and proposes adaptive control strategies to mitigate the effects of network degradation, thereby optimizing the reliability and efficiency of next-generation warehouse robotic systems.

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