most citedFast CRDNN: Towards on Site Training of Mobile Construction Machines

6 citations · 12 across the 5 of their papers we have counts for

collaborators

6 papers

cs.RO2021

KIT Bus: A Shuttle Model for CARLA Simulator

Yusheng Xiang, Shuo Wang, Tianqing Su +3

With the continuous development of science and technology, self-driving vehicles will surely change the nature of transportation and realize the automotive industry's transformatio…

cs.AI2021

An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution

Yusheng Xiang, Kailun Liu, Tianqing Su +4

Multi working-machines pathfinding solution enables more mobile machines simultaneously to work inside of a working site so that the productivity can be expected to increase evolut…

cs.RO20201 cited

Where am I? SLAM for Mobile Machines on A Smart Working Site

Yusheng Xiang, Dianzhao Li, Tianqing Su +4

The current optimization approaches of construction machinery are mainly based on internal sensors. However, the decision of a reasonable strategy is not only determined by its int…

cs.NI2020

5G meets Construction Machines: Towards a Smart working Site

Yusheng Xiang, Bing Xu, Tianqing Su +3

The fleet management of mobile working machines with the help of connectivity can increase safety and productivity. Although in our previous study, we proposed a solution to use IE…

cs.CV20205 cited

KIT MOMA: A Mobile Machines Dataset

Yusheng Xiang, Hongzhe Wang, Tianqing Su +4

Mobile machines typically working in a closed site, have a high potential to utilize autonomous driving technology. However, vigorously thriving development and innovation are happ…

eess.SP20206 cited

Fast CRDNN: Towards on Site Training of Mobile Construction Machines

Yusheng Xiang, Tian Tang, Tianqing Su +4

The CRDNN is a combined neural network that can increase the holistic efficiency of torque based mobile working machines by about 9% by means of accurately detecting the truck load…