Autonomous Control, Waypoint Navigation, and a Real-Time UAV Video Database

2012 ◽  
Author(s):  
Chhabilal Adhikari ◽  
Peter Baumann ◽  
Saksham Gautam
Keyword(s):  
Real Time ◽  
Autonomous Control ◽  
Video Database ◽  
Waypoint Navigation

Autonomous Control of Abrasive Flow Precision Machining

2011 ◽  
Vol 215 ◽  
pp. 384-388
Author(s):  
J.L. Xu ◽  
Shi Ming Ji ◽  
Z.P. Fang
Keyword(s):  
Real Time ◽  
Control Program ◽  
Autonomous Control ◽  
Network Communication ◽  
Precision Machining ◽  
Motor Speed ◽  
Communication Structure ◽  
Quality And Reliability ◽  
Autonomous Nodes ◽  
Program Reliability

Autonomous nodes distribution, including their relations, real time quality and network communication in abrasive flow precision machining (AFPM) was studied. Autonomous nodes are arranged according to their function. Control program of motor speed is copied into liquid level nodes, pressure nodes, temperature nodes, flux nodes and input/output nodes. If nodes failure has happened, competition algorithm is enabled automatically to select a new node to run important program. Reliability of autonomous control system can be calculated utilizing the formula derived from probability theory. ARM 9 embedded systems with 32 bit CPU and real time embedded operating system are adopted to realize real time quality and reliability of nodes which run independently. CAN field bus and message type flag are used in network communication structure to ensure the real time quality and reliability of nodes connection. Results reveal that using autonomous decentralized control in AFPM possesses not only the characteristic of real time quality, but also the online fault tolerance, which can ensure that system runs continuously even if some nodes break down. The method can avoid system destruction and improve whole system reliability.

Real-time Autonomous Control

1993 ◽  
Vol 26 (2) ◽  
pp. 577-580 ◽  
Author(s):  
A.J. Krijgsman ◽  
R. Jager ◽  
H.B. Verbruggen
Keyword(s):  
Real Time ◽  
Autonomous Control ◽  
Time Autonomous

Recovery of atom density drift caused by change in reactor wall conditions by real-time autonomous control

2014 ◽  
Vol 47 (42) ◽  
pp. 422002 ◽  
Author(s):  
Toshiya Suzuki ◽  
Kenji Ishikawa ◽  
Keigo Takeda ◽  
Hiroki Kondo ◽  
Makoto Sekine ◽  
...  
Keyword(s):  
Real Time ◽  
Autonomous Control ◽  
Reactor Wall ◽  
Atom Density ◽  
Time Autonomous

Model-Free Real-Time Autonomous Control for a Residential Multi-Energy System Using Deep Reinforcement Learning

2020 ◽  
Vol 11 (4) ◽  
pp. 3068-3082 ◽  
Author(s):  
Yujian Ye ◽  
Dawei Qiu ◽  
Xiaodong Wu ◽  
Goran Strbac ◽  
Jonathan Ward
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Energy System ◽  
Autonomous Control ◽  
Model Free ◽  
Time Autonomous

Low SWaP real-time edge processing for cognitive sensing and autonomous control applications

2021 ◽  
Author(s):  
Sanaz Adl ◽  
Adour Kabakian ◽  
Peter Petre ◽  
Austin Garrido
Keyword(s):  
Real Time ◽  
Autonomous Control ◽  
Control Applications

scholarly journals Smart Mobility and Aspects of Vehicle-to-Infrastructure: A Data Viewpoint

2021 ◽  
Vol 11 (22) ◽  
pp. 10514
Author(s):  
Boris Bučko ◽  
Martin Michálek ◽  
Katarína Papierniková ◽  
Katarína Zábovská
Keyword(s):  
Real Time ◽  
Automotive Industry ◽  
Autonomous Vehicles ◽  
Historical Development ◽  
Autonomous Control ◽  
Decision Making Process ◽  
Process Data ◽  
Multiple Sensors ◽  
Vehicle To Infrastructure ◽  
Smart Mobility

The aim of this article is to describe estimates of data difficulty and aspects of the data viewpoint within Vehicle-to-Infrastructure (V2I) communication in the Smart Mobility concept. The historical development of the database system’s architecture, that stores and processes a larger amount of data, is currently sufficient and effective for the needs of today’s society. The goal of vehicle manufacturers is the continual increase in driving comfort and the use of multiple sensors to sense the vehicle’s surroundings, as well as to help the driver in critical situations avoid danger. The increasing number of sensors is directly related to the amount of data generated by the vehicle. In the automotive industry, it is crucial that autonomous vehicles can process data in real time or can locate itself in precise accuracy, for the decision-making process. To meet these requirements, we will describe HD maps as a key segment of autonomous control. It alerts the reader to the need to address the issue of real-time Big Data processing, which represents an important role in the concept of Smart Mobility.

Autonomous control system and real-time simulation platform for UAV

2006 ◽  
Author(s):  
Yan Zhang ◽  
Rui Zhou ◽  
Zhouyi Yu ◽  
Zongji Chen
Keyword(s):  
Control System ◽  
Real Time ◽  
Autonomous Control ◽  
Simulation Platform ◽  
Real Time Simulation ◽  
Time Simulation
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