Federated Learning for Vision-based Obstacle Avoidance in the Internet of Robotic Things-Reference-Cited by-同舟云学术

Federated Learning for Vision-based Obstacle Avoidance in the Internet of Robotic Things

Published:2022-12-12 Issue: Volume: Page:
ISSN:
Container-title:2022 Seventh International Conference on Fog and Mobile Edge Computing (FMEC)
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Author:

Yu Xianjia¹,Queralta Jorge Peña¹,Westerlund Tomi¹

Affiliation:

1. University of Turku,Turku Intelligent Embedded and Robotic Systems (TIERS) Lab,Finland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10062346/10062491/10062657.pdf?arnumber=10062657

Reference28 articles.

1. A Vision-based Irregular Obstacle Avoidance Framework via Deep Reinforcement Learning

2. Memory-Based Deep Reinforcement Learning for Obstacle Avoidance in UAV With Limited Environment Knowledge

3. Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning

4. Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

5. Analyzing general-purpose deep-learning detection and segmentation models with images from a lidar as a camera sensor;xianjia;International Conference on Intelligent Systems Design and Engineering Applications Lecture Notes in Electrical Engineering (to appear),2022

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1. Make Federated Learning a Standard in Robotics by Using ROS2;Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies;2023-12-04

2. Aggregation Mechanisms in Federated Learning for Enhancing Robotic Visual Obstacle Avoidance;2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI);2023-12-01