AFR: An Efficient Buffering Algorithm for Cloud Robotic Systems

Communication between robots and the server is a major problem for cloud robotic systems. In this paper, we address the problem caused by data loss during such communications and propose an efficient buffering algorithm, called AFR, to solve the problem. We model the problem into an optimization problem to maximize the received Quantity of Information (QoI). Our AFR algorithm is formally proved to achieve near-optimal QoI, which has a lower bound that is a constant multiple of the unrealizable optimal QoI. We implement our AFR algorithm in ROS without changing the API for the applications. Our experiments on two cloud robot applications show that our AFR algorithm can efficiently and effectively reduce the impact of data loss. For the remote mapping application, the RMSE caused by data loss can be reduced by about 20%. For the remote tracking application, the probability of tracking failure caused by data loss can be reduced from about 40 %-60 % to under 10%. Meanwhile, our AFR algorithm introduces time overhead of under 10 microseconds.

Authors

• Yu-Ping Wang 0001
• Hao-Ning Wang
• Zi-Xin Zou
• Dinesh Manocha

Keywords

• Systems architecture
• Data models
• Servers
• Robots
• Optimization
• Intelligent robots
• Efficient Algorithm
• Robotic System
• Cloud Robotics
• Root Mean Square Error
• Amount Of Information
• Data Loss
• Robotic Applications
• Time Overhead
• Robot Operating System
• Tracking Applications
• Remote Applications
• Tracking Failure
• Service Quality
• Horizontal Axis
• Frame Rate
• Wireless Networks
• Color Images
• Mapping Algorithm
• Depth Images
• 3D Point
• Queue Size
• Drop Rate
• Network Bandwidth
• Tracking Algorithm
• Part Of Wall
• Depth Camera
• Multiple Robots
• Adjacent Images
• Negligible Overhead