simulation

With MultibodyPlant, why do I get `SolveQuadraticForTheSmallestPositiveRoot(): condition 'Delta > 0' failed`?

此生再无相见时 提交于 2020-05-29 09:53:46
问题 (This is from a Drake Slack conversation.) I'm playing with an "exploding IIWA" demo to prototype some workflows with MultibodyPlant and SceneGraph . Basically, I'm just adding a robot arm that has articulation (revolute joints between multiple links) and dropping the robot arm from a height. When it hits a certain point, I want to pause the simulation, remove all of the joints, and the resume the simulation. Here is the code that I am working with (which needs some Drake PRs at present to

With MultibodyPlant, why do I get `SolveQuadraticForTheSmallestPositiveRoot(): condition 'Delta > 0' failed`?

我与影子孤独终老i 提交于 2020-05-29 09:53:08
问题 (This is from a Drake Slack conversation.) I'm playing with an "exploding IIWA" demo to prototype some workflows with MultibodyPlant and SceneGraph . Basically, I'm just adding a robot arm that has articulation (revolute joints between multiple links) and dropping the robot arm from a height. When it hits a certain point, I want to pause the simulation, remove all of the joints, and the resume the simulation. Here is the code that I am working with (which needs some Drake PRs at present to

Latitude/Longitude Generation to be used as sample data

一世执手 提交于 2020-05-26 17:57:24
问题 I am writing a demo web application that tracks multiple devices through my companies platform. I have the app working, but need a csv file that will simulate devices moving on a map as if they were a tracker attached to a car. The simulator works by reading 1 row of data every second (1 lat/lng point). Here is an example of the first few lines of a file that would work if the points weren't scattered across the US (the SclId is the device name). SclId Latitude Longitude HAT-0 44.968046 -94

R: Problem with MonteCarlo Simulation and Normal Distribution

倾然丶 夕夏残阳落幕 提交于 2020-05-14 03:33:35
问题 I am trying to solve the following exercise: Let Z_n be maximum of n standard normal observations. Estimate what n should be so that P(Z_n>4)=0.25 I have tried following code and I know the answer is about n=9000 because it returns aproximately 0.25. I should change my code so that n is the output and not the input. n=9000 x1 <- sapply(1:n, function(i){max(rnorm(n=n,0,1))}) length(x1[x1>4])/length(x1) How can I do that? Thanks for helping! 回答1: Well, you could select appropriate range and

R: Problem with MonteCarlo Simulation and Normal Distribution

核能气质少年 提交于 2020-05-14 03:31:39
问题 I am trying to solve the following exercise: Let Z_n be maximum of n standard normal observations. Estimate what n should be so that P(Z_n>4)=0.25 I have tried following code and I know the answer is about n=9000 because it returns aproximately 0.25. I should change my code so that n is the output and not the input. n=9000 x1 <- sapply(1:n, function(i){max(rnorm(n=n,0,1))}) length(x1[x1>4])/length(x1) How can I do that? Thanks for helping! 回答1: Well, you could select appropriate range and

Lotka Volterra with Runge Kutta not desired precision

大兔子大兔子 提交于 2020-05-13 13:57:25
问题 Population over time (should be the same height at every peak I've programmed a code to simulate a mice and fox population using Runge-Kutta 4th order. But the result is not as wanted to be.. each peak should nearly be at same height I don't think that it is a problem of step size.. Do you have an idea? import matplotlib.pyplot as plt import numpy as np #function definition def mice(f_0, m_0): km = 2. #birthrate mice kmf = 0.02 #deathrate mice return km*m_0 - kmf*m_0*f_0 def fox(m_0, f_0): kf

Simulation Speed of Nonlinear Solver in Modelica

怎甘沉沦 提交于 2020-04-14 19:05:42
问题 Why does Modelica's nonlinear solver oneSolveNonlinearEquation take more time to solve a nonlinear equation than traditional fixed point iterative (FPI) scheme? The equation y= arctan(1-x/1+x)-x solved by the oneSolveNonlinearEquation solver (which basically uses Brent's Method) solves the above equation in 6 iterations whereas traditional iterative approach takes 111 iterations. However, the CPU time taken by the iterative scheme is lesser than that taken by the oneSolveNonlinearEquation

How to install IMUsim

馋奶兔 提交于 2020-03-18 05:17:20
问题 This a guide rather than a question, because I spent a LOT of time fighting with compilation errors when installing IMUsim, and I know that many other researchers have struggled. The IMUsim code is currently unmaintained and the installation documentation is lacking. If you simply clone the current IMUsim repo and follow the instructions to build from source, it will fail citing missing files. See my answer below for the solution. 回答1: Installation instructions First, download the repo: git

Simulate keystroke in Linux with Python

非 Y 不嫁゛ 提交于 2020-03-07 07:12:26
问题 How can I simulate a keystroke in python? I also want to press multiple keys simultaneously. Something like: keystroke('CTRL+F4') or keystroke('Shift+A') 回答1: Although it's specific to X, you can install the xautomation package ( apt-get install xautomation on Debian-based systems) and use xte to simulate keypresses, e.g.: from subprocess import Popen, PIPE control_f4_sequence = '''keydown Control_L key F4 keyup Control_L ''' shift_a_sequence = '''keydown Shift_L key A keyup Shift_L ''' def

Simulate keystroke in Linux with Python

不羁岁月 提交于 2020-03-07 07:10:00
问题 How can I simulate a keystroke in python? I also want to press multiple keys simultaneously. Something like: keystroke('CTRL+F4') or keystroke('Shift+A') 回答1: Although it's specific to X, you can install the xautomation package ( apt-get install xautomation on Debian-based systems) and use xte to simulate keypresses, e.g.: from subprocess import Popen, PIPE control_f4_sequence = '''keydown Control_L key F4 keyup Control_L ''' shift_a_sequence = '''keydown Shift_L key A keyup Shift_L ''' def