activity
20202022
most citedAutonomous Heavy-Duty Mobile Machinery: A Multidisciplinary Collaborative Challenge

14 citations · 31 across the 10 of their papers we have counts for

collaborators

10 papers

cs.HC2022★ 14 cited

Autonomous Heavy-Duty Mobile Machinery: A Multidisciplinary Collaborative Challenge

Tyrone Machado, David Fassbender, Abdolreza Taheri +10

Heavy-duty mobile machines (HDMMs) are a wide range of machinery used in diverse and critical application areas which are currently facing several issues like skilled labor shortag…

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★ 2 cited

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.RO2020★ 1 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.CV2020★ 5 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.SP2020★ 6 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…

eess.SY2020★ 1 cited

A novel Algorithm for Hydrostatic-mechanical Mobile Machines with a Dual-Clutch Transmission

Yusheng Xiang, Ruoyu Li, Christine Brach +2

Mobile machines using a hydrostatic transmission is highly efficient under lower working-speed condition but less capable at higher transport velocities. To enhance overall efficie…

cs.NI2020

Realtime Estimation of IEEE 802.11p for Mobile working Machines Communication respecting Delay and Packet Loss

Yusheng Xiang, Tianqing Su, Xiaole Liu +1

The fleet management of mobile working machines with the help of connectivity can increase not only safety but also productivity. However, rare mobile working machines have taken a…

eess.SP2020★ 2 cited

Optimization of Operation Strategy for Primary Torque based hydrostatic Drivetrain using Artificial Intelligence

Yusheng Xiang, Marcus Geimer

A new primary torque control concept for hydrostatics mobile machines was introduced in 2018. The mentioned concept controls the pressure in a closed circuit by changing the angle…