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[ Home | Blogs | Events | Robots | Humans | Projects | Podcasts | About | Account ]For those of you getting started with ROS, I have written up a do-it-yourself tutorial for tracking a colored object using a web cam and AX-12 pan and tilt servos. You can find it here:
ROS by Example: Visual Object Tracking
In this short article on using SLAM with ROS, I have posted a couple of videos showing Pi Robot mapping out part of an apartment using a Hokuyo laser scanner and the gmapping package. See
http://www.pirobot.org/blog/0015/
For the past several months, I have been learning the basics of ROS from Willow Garage. At the same time, I have been testing Mike Ferguson's "Poor Man's Lidar" or PML as an alternative to a more expensive laser range finder. The results are encouraging--at least for obstacle avoidance and simple navigation tasks. You can see the report at:
http://www.pirobot.org/blog/0014/
I recently converted most of the C# code for my Pi Robot project to Python. At the same time, I am changing the programming architecture to use message passing among nodes. To get started, I wrote up a little introduction to the topic at:

I finally had a chance to write up the math behind the Pi Robot arm tracking video. Keep in mind that I am only using the two shoulder joints in each arm--the elbow and wrist servos are fixed--so the inverse kinematics is fairly straightforward. Later on I'll have to deal with the other joints...
Here is the link to the write-up:
http://www.pirobot.org/blog/0011/
--patrick
Here is a followup video to my previous blog entry. In this video, a number of independent behavioral threads are running to enable the robot to track and grasp the green balloon. Whenever the balloon is grasped, the robot turns its attention to the red balloon. When the green balloon is released, tracking turns again to it and the red balloon is ignored. I use RoboRealm to do the green/red tracking. There is a sonar sensor on the inside of the left hand that tells the robot when something is ready to be grasped. It can also do this using vision alone along with some trigonometry, but the result is more reliable when using the sensor.
--patrick
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