Modern information technologies and the advent of machines powered by artificial
intelligence (AI) have already strongly influenced the world of work in the 21st century.
Computers, algorithms and software simplify everyday tasks, and it is impossible
to imagine how most of our life could be managed without them. However, is it
also impossible to imagine how most process steps could be managed without
human force? The information economy characterised by exponential growth
replaces the mass production industry based on economy of scales
In this book for the optimisation of assembly conveyor lines we are dealing with series part production
featured by a medium complexity degree and a medium number of individual components and assembly
technique alternatives. Modern production techniques for medium to large series products or mass
production usually involve assembly conveyor lines. They still use hand labour more or less automated.
The aim is to have monotonous and similar in type operations or such causing fatigue, stress and
production traumas, gradually replaced by automated assembly cycles, means and techniques. This
usually widely involves industrial robots and handlers. Higher productivity, lower cost and higher quality
of assembled products are usually required.
Surface profile measurement by noncontact optical methods has been extensively studied because of its importance in automated manufacturing, component quality control, medicine, and robotics. In most of these methods a known periodic pattern,
Instead of finding the longest common
subsequence, let us try to determine the
length of the LCS.
Then tracking back to find the LCS.
Consider a1a2…am and b1b2…bn.
Case 1: am=bn. The LCS must contain am,
we have to find the LCS of a1a2…am-1 and
b1b2…bn-1.
Case 2: am≠bn. Wehave to find the LCS of
a1a2…am-1 and b1b2…bn, and a1a2…am and
b b b
b1b2…bn-1
Let A = a1 a2 … am and B = b1 b2 … bn
Let Li j denote the length of the longest i,g g
common subsequence of a1 a2 … ai and b1 b2
… bj.
Li,j = Li-1,j-1 + 1 if ai=bj
max{ L L } a≠b i-1,j, i,j-1 if ai≠j
L0,0 = L0,j = Li,0 = 0 for 1≤i≤m, 1≤j≤n.
object recognition using fast adaptive hough transform 快速自適應(yīng)霍夫變換
作者：D.D. Haule. A.S. Malowany
Computer Vision and Robotics Laboratory
Department of Electrical Engineering
McGill University。IEEE 1989的文章，對指導(dǎo)霍夫變換檢測目標(biāo)的識別有一定的參考意義
This book describes a unifying framework to networked teleoperation systems
cutting across multiple research fields including networked control system for linear
and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral
teleoperation, cooperative teleoperation, and some teleoperation application
examples. Networked control has been deeply studied at the intersection of systems
& control and robotics for a long time, and many scholarly books on the topic have
been already published. Nevertheless, the approach remains active even in several
new research fields, such as bilateral teleoperation, single master and multiple
slaves, trilateral teleoperation, and multilateral teleoperation
