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2017-02-22 09:25:34 -0500 received badge  Organizer (source)
2017-02-22 09:23:33 -0500 asked a question Calculation of center point for the localization of robot in 3D data

I am trying to find a reliable method to calculate the corner points of a container. From these corner point’s idea is to calculate the center point of the container for the localization of robot, it means that the calculated center point will be the destination of robot in order to pick the container. For this I am looking for any suggestions to calculate the corner points or may be if any possibility to calculate the center point directly. Up to this point PCL library C/C++ is used for the processing of the 3D data. The image below is the screenshot of the container. thanks in advance.


2016-11-17 03:09:39 -0500 received badge  Enthusiast
2016-11-16 03:27:10 -0500 asked a question point cloud alignment using features and icp

Hello guys,

I am using icp/PCL. I assumed that the icp is providing the convergence and transformation matrix correctly for the alignment of measured and model pointcloud data for a particular object. My question is, once I have this Final transformation matrix how I could use it further to localize my robot. Is that transformation matrix tells how Robot has to translate and rotate so that it can approach the particular object ? Secondly, For the initial alignment I am interested to use feature based initial alignment but not sure with which method to start with ? any suggestions please

Any tutorial addressing this will be valued and highly appreciated.

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2016-05-29 15:10:15 -0500 commented answer 3D Camera Selection

the target trolley here in the following picture link text

How much this IDS sensor cost ?

2016-05-29 12:43:17 -0500 asked a question 3D Camera Selection

For an robotic application which requires 24/7 working in an indoor environment picking up boxes ( after recognizing using the camera application), loading the boxes, drop them at the defined location.

I am looking for an industrial camera solution, initially I decided to go for Sick 3Vistor-T (TOF) before I start with this I want to be sure.

Any suggestions which will be an appropriate solution here in this case ?

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2016-05-09 06:19:11 -0500 commented answer ROS Installation, Unable to locate package ros indigo

Thanks alot. so now I am heading to 14.04 :)

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2016-05-08 17:38:19 -0500 commented question ROS Installation, Unable to locate package ros indigo

ubuntu 16.04 LTS on x86_64

2016-05-08 17:17:27 -0500 commented question ROS Installation, Unable to locate package ros indigo

yes sure :) 1.2 , 1.3, and at Desktop Full install I m having this problem.

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2016-05-08 16:36:20 -0500 asked a question ROS Installation, Unable to locate package ros indigo


I followed this ROS installation tutorial ( unfortunately at Desktop full install following error appeared.

sudo apt-get install ros-indigo-desktop-full

Reading package lists... Done

Building dependency tree

Reading state information... Done

E: Unable to locate package ros-indigo-desktop-full

How can I solve this problem ?

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2016-04-19 13:06:17 -0500 commented answer 3D Camera Selection

Great! I understand. Thank you so much.

2016-04-19 11:19:12 -0500 commented question 3D Camera Selection

@NEngelhard Lets say for camera part, 300-400$ ?

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2016-04-19 10:16:09 -0500 commented question 3D Camera Selection

ok thanks :)

2016-04-19 09:25:58 -0500 asked a question 3D Camera Selection

I am working on a robot which will pick items from Point A and deliver it to Point B. For this purpose I planned to use a 3D camera and plan the strategy as follows.

  1. Selection of 3D camera [Stereo, TOF or Structured light, Please suggest which one will be the suitable solution?]

  2. Generation of Dense 3D point cloud data, [ By fusion of Laser scanner data and the camera data]

  3. Filter and feature extraction from data , Obstacle avoidance , path planning from Point A to Point B.

If there is any tutorial available which matches with my goals it would be great. Which steps are missing in my strategy ?

Thankyou in advance