# Neuromorphic Event-Based Slip Detection and suppression in Robotic Grasping and Manipulation

arXiv: https://arxiv.org/abs/2004.07386 · HTML: https://mlsanity.com/paper/2004.07386/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2020.

## Built on by (most cited first, 9 of 9)

- [Evetac: An Event-based Optical Tactile Sensor for Robotic Manipulation](https://mlsanity.com/paper/2312.01236/) (2023)
- [A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment](https://mlsanity.com/paper/2302.06301/) (2023)
- [Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack](https://mlsanity.com/paper/2404.03325/) (2024)
- [Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Grasping](https://mlsanity.com/paper/2303.11228/) (2023)
- [Combined Physics and Event Camera Simulator for Slip Detection](https://mlsanity.com/paper/2503.04838/) (2025)
- [Intelligent machines work in unstructured environments by differential neuromorphic computing](https://mlsanity.com/paper/2309.08835/) (2023)
- [SGED: A Benchmark dataset for Performance Evaluation of Spiking Gesture Emotion Recognition](https://mlsanity.com/paper/2304.14714/) (2023)
- [A model-free approach to fingertip slip and disturbance detection for grasp stability inference](https://mlsanity.com/paper/2311.13245/) (2023)
- [An Adaptive Grasping Force Tracking Strategy for Nonlinear and Time-Varying Object Behaviors](https://mlsanity.com/paper/2412.02335/) (2024)

## Abstract (arXiv)

Slip detection is essential for robots to make robust grasping and fine manipulation. In this paper, a novel dynamic vision-based finger system for slip detection and suppression is proposed. We also present a baseline and feature based approach to detect object slips under illumination and vibration uncertainty. A threshold method is devised to autonomously sample noise in real-time to improve slip detection. Moreover, a fuzzy based suppression strategy using incipient slip feedback is proposed for regulating the grip force. A comprehensive experimental study of our proposed approaches under uncertainty and system for high-performance precision manipulation are presented. We also propose a slip metric to evaluate such performance quantitatively. Results indicate that the system can effectively detect incipient slip events at a sampling rate of 2kHz (Delta t = 500μ s) and suppress them before a gross slip occurs. The event-based approach holds promises to high precision manipulation task requirement in industrial manufacturing and household services.