A Dynamically Adapting Network Programming Framework

2011 ◽  
Author(s):  
Ben Wun ◽  
Mike Wilson ◽  
Patrick Crowley
Keyword(s):  
Network Programming ◽  
Programming Framework

EasiSNP: A Sensor Network Programming Framework Based on Spatiotemporal Attributes

2014 ◽  
Vol 36 (12) ◽  
pp. 2390-2405
Author(s):  
Jie-Fan QIU ◽  
Dong LI ◽  
Hai-Long SHI ◽  
Li CUI
Keyword(s):  
Sensor Network ◽  
Network Programming ◽  
Programming Framework

Co-evolution of Hetero Multiagent Systems using Genetic Network Programming.

2003 ◽  
Vol 123 (3) ◽  
pp. 544-551 ◽  
Author(s):  
Kotaro Hirasawa ◽  
Masafumi Okubo ◽  
Jinglu Hu ◽  
Junichi Murata ◽  
Yuko Matsuya
Keyword(s):  
Multiagent Systems ◽  
Genetic Network ◽  
Network Programming ◽  
Genetic Network Programming

Buying and Selling Stocks of Multi Brands Using Genetic Network Programming with Control Nodes

2008 ◽  
Vol 128 (12) ◽  
pp. 1811-1819 ◽  
Author(s):  
Etsushi Ohkawa ◽  
Yan Chen ◽  
Zhiguo Bao ◽  
Shingo Mabu ◽  
Kaoru Shimada ◽  
...  
Keyword(s):  
Genetic Network ◽  
Network Programming ◽  
Genetic Network Programming

scholarly journals Vertical Jumping for Legged Robot Based on Quadratic Programming

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3679
Author(s):  
Dingkui Tian ◽  
Junyao Gao ◽  
Xuanyang Shi ◽  
Yizhou Lu ◽  
Chuzhao Liu
Keyword(s):  
Quadratic Programming ◽  
Stance Phase ◽  
Center Of Mass ◽  
Maximum Error ◽  
Legged Robot ◽  
Flight Phase ◽  
Programming Framework ◽  
Vertical Jumping ◽  
Control Schemes ◽  
And Control

The highly dynamic legged jumping motion is a challenging research topic because of the lack of established control schemes that handle over-constrained control objectives well in the stance phase, which are coupled and affect each other, and control robot’s posture in the flight phase, in which the robot is underactuated owing to the foot leaving the ground. This paper introduces an approach of realizing the cyclic vertical jumping motion of a planar simplified legged robot that formulates the jump problem within a quadratic-programming (QP)-based framework. Unlike prior works, which have added different weights in front of control tasks to express the relative hierarchy of tasks, in our framework, the hierarchical quadratic programming (HQP) control strategy is used to guarantee the strict prioritization of the center of mass (CoM) in the stance phase while split dynamic equations are incorporated into the unified quadratic-programming framework to restrict the robot’s posture to be near a desired constant value in the flight phase. The controller is tested in two simulation environments with and without the flight phase controller, the results validate the flight phase controller, with the HQP controller having a maximum error of the CoM in the x direction and y direction of 0.47 and 0.82 cm and thus enabling the strict prioritization of the CoM.

An Intermediate Representation for Network Programming Languages

2020 ◽  
Author(s):  
Hao Li ◽  
Peng Zhang ◽  
Guangda Sun ◽  
Chengchen Hu ◽  
Danfeng Shan ◽  
...  
Keyword(s):  
Programming Languages ◽  
Intermediate Representation ◽  
Network Programming
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