Titlebook: Nachhaltigkeitsmanagement für Logistikdienstleister; Ein Praxisleitfaden Dirk Lohre,Roland Pfennig,Ruben Gotthardt Book 2015 Springer Fachm

改變立場

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardtechnology and Applications (RiTA 2013) held in Denver on DecWe are facing a new technological challenge on how to store and retrieve knowledge and manipulate intelligence for autonomous services by intelligent systems which should be capable of carrying out real world tasks autonomously. To address

輕浮思想

人工制品

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardtoose soil, steep slope etc. There are some technologies that large obstacles such as stones can be avoided by using cameras or lasers. However, it is extremely difficult for rovers to traverse loose soil, especially “l(fā)oose soil with steep slope”. If the area being traversed is sloped, these rovers m

微生物

chnology and Applications (RiTA 2012) held in Gwangju, KoreaIn recent years, robots have been built based on cognitive architecture which has been developed to model human cognitive ability. The cognitive architecture can be a basis for intelligence technology to generate robot intelligence. In this

好開玩笑

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardtonment. Based on SURF (Speed Up Robust Features) descriptor, the proposed algorithm generates 3-D feature points incorporating depth information into RGB color information. By using an IMU, the generated 3-D feature points are rotated in order to have the same rigid body rotation component between t

mortuary

脊椎動物

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardtd be made in advance or concurrently. It is important to know an accurate position for the accurate world modeling. The aim of this paper is an accurate localization method for the world modeling under the situation where the portion of signals from global positioning system (GPS) satellites is bloc

串通

–FER

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardtriving Car system. The system is capable of autonomously driving in places where there is a color difference between the road and the footpath/roadside, especially in gardens/parks. On the basis of the digital image-processing algorithm, which resulted into optimal operation of the self-driving car

ARK

Dirk Lohre,Roland Pfennig,Viktoria Poerschke,Ruben Gotthardt performance of the network on task after training, and total time and steps required to train. The neural network is trained for 10 different sizes of batch with other hyper parameter values fixed. The network is able to carry out the cart-pole task with the probability of 0.99 or more with the bat