Distributed Client-Server Optimization for SLAM with Limited On-Device Resources

by   Yetong Zhang, et al.

Simultaneous localization and mapping (SLAM) is a crucial functionality for exploration robots and virtual/augmented reality (VR/AR) devices. However, some of such devices with limited resources cannot afford the computational or memory cost to run full SLAM algorithms. We propose a general client-server SLAM optimization framework that achieves accurate real-time state estimation on the device with low requirements of on-board resources. The resource-limited device (the client) only works on a small part of the map, and the rest of the map is processed by the server. By sending the summarized information of the rest of map to the client, the on-device state estimation is more accurate. Further improvement of accuracy is achieved in the presence of on-device early loop closures, which enables reloading useful variables from the server to the client. Experimental results from both synthetic and real-world datasets demonstrate that the proposed optimization framework achieves accurate estimation in real-time with limited computation and memory budget of the device.


page 1

page 2

page 3

page 4


Keeping Less is More: Point Sparsification for Visual SLAM

When adapting Simultaneous Mapping and Localization (SLAM) to real-world...

Embedded Systems Architecture for SLAM Applications

In recent years, we have observed a clear trend in the rapid rise of aut...

Augmenting Visual SLAM with Wi-Fi Sensing For Indoor Applications

Recent trends have accelerated the development of spatial applications o...

SLAMCast: Large-Scale, Real-Time 3D Reconstruction and Streaming for Immersive Multi-Client Live Telepresence

Real-time 3D scene reconstruction from RGB-D sensor data, as well as the...

Improved Signed Distance Function for 2D Real-time SLAM and Accurate Localization

Accurate mapping and localization are very important for many industrial...

Collaborative Visual Inertial SLAM for Multiple Smart Phones

The efficiency and accuracy of mapping are crucial in a large scene and ...

RDSP: Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management

In post-disaster scenarios, such as after floods, earthquakes, and in wa...