mlsanityData to 7 Oct 2026

A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms

arXiv 2209.03511 ↗First posted 8 Sep 2022cs.RO cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Robotic arms are widely used in automatic industries. However, with wide applications of deep learning in robotic arms, there are new challenges such as the allocation of grasping computing power and the growing demand for security. In this work, we propose a robotic arm grasping approach based on deep learning and edge-cloud collaboration. This approach realizes the arbitrary grasp planning of the robot arm and considers the grasp efficiency and information security. In addition, the encoder and decoder trained by GAN enable the images to be encrypted while compressing, which ensures the security of privacy. The model achieves 92% accuracy on the OCID dataset, the image compression ratio reaches 0.03%, and the structural difference value is higher than 0.91.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 39 references that are in the map. First posted on arXiv 8 Sep 2022.

Builds on

17 of 39 references.

References · 17

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
  4. 2018Variational image compression with a scale hyperpriorcited by 910
  5. 2016Full Resolution Image Compression with Recurrent Neural Networkscited by 170
  6. 2015Variable Rate Image Compression with Recurrent Neural Networkscited by 168
  7. 2017Real-Time Adaptive Image Compressioncited by 127
  8. 2019Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systemscited by 77
  9. 2019EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasetscited by 58
  10. 2016Robotic Grasp Detection using Deep Convolutional Neural Networkscited by 47
  11. 2021End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGBcited by 44
  12. 2018Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methodscited by 32
5 more
  1. 2019Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Datacited by 24
  2. 2020Peer-Assisted Robotic Learning: A Data-Driven Collaborative Learning Approach for Cloud Robotic Systemscited by 9
  3. 2015Guiding Long-Short Term Memory for Image Caption Generationcited by 8
  4. 2021Online Meta Adaptation for Variable-Rate Learned Image Compressioncited by 3
  5. 2022ElasticROS: An Elastically Collaborative Robot Operation System for Fog and Cloud Roboticscited by 3

Built on by

Not cited yet.