Since October 2007 I developed new object recognition algorithm "Associative Video Memory" (AVM).
Algorithm AVM uses a principle of multilevel decomposition of recognition matrices, it is steady against noise of the camera and well scaled, simply and quickly for training.
And now I want to introduce my experiment with robot navigation based on visual landmark beacons: "Follow me" and "Walking by gates".
I embodied both algorithms to Navigator plugin for using within RoboRealm software.
The Navigator module has two base algorithms:
-= Follow me =-
The navigation algorithm do attempts to align position of a tower and the body of robot on the center of the first recognized object in the list of tracking and if the object is far will come nearer and if it is too close it will be rolled away back.
-= Walking by gates =-
The gate data contains weights for the seven routes that indicate importance of this gateway for each route. At the bottom of the screen was added indicator "horizon" which shows direction for adjust the robot's motion for further movement on the route. Field of gates is painted blue if the gates do not participate in this route (weight rate 0), and warmer colors (ending in yellow) show a gradation of "importance" of the gate in the current route.
* The procedure of training on route
For training of the route you have to indicate actual route (button "Walking by way") in "Nova gate" mode and then you must drive the robot manually by route (the gates will be installed automatically). In the end of the route you must click on the button "Set checkpoint" and then robot will turn several times on one spot and mark his current location as a checkpoint.
So, if robot will walk by gates and suddenly will have seen some object that can be recognized then robot will navigate by the "follow me" algorithm.
If robot can't recognize anything (gate/object) then robot will be turning around on the spot for searching (it may twitch from time to time in a random way).
For more information see also thread: "Autonomous robot's navigation" at Trossen Robotics.
Now AVM Navigator v0.7 is released and you can download it from RoboRealm website.
In new version is added two modes: "Marker mode" and "Navigate by map".
Marker mode
Marker mode provides a forming of navigation map that will be made automatically by space marking. You just should manually lead the robot along some path and repeat it several times for good map detailing.
Navigation by map
In this mode you should point the target position at the navigation map and further the robot plans the path (maze solving) from current location to the target position (big green circle) and then robot begins automatically walking to the target position.
For external control of “Navigate by map” mode is added new module variables:
NV_LOCATION_X - current location X coordinate;
NV_LOCATION_Y - current location Y coordinate;
NV_LOCATION_ANGLE - horizontal angle of robot in current location (in radians);
Target position at the navigation map
NV_IN_TRG_POS_X - target position X coordinate;
NV_IN_TRG_POS_Y - target position Y coordinate;
NV_IN_SUBMIT_POS - submitting of target position (value should be set 0 -> 1 for action).
Examples
Quake 3 Mod
Don’t have a robot just yet? Then click here to view the manual that explains how to setup RoboRealm with the AVM module to control the movement and processing of images from the Quake first person video game. This allows you to work with visual odometry techniques without needing a robot!
The additional software needed for this integration can be downloaded here.
Is it possible to play with virtual robot in “Navigation by map” mode?
Yes!
Just look into documentation and download the “AVM Quake 3 mod” installation.
Next modification of AVM Navigator v0.7.2.1 is released.
Changes:
Visual odometry algorithm was updated:
I have done new plugin for RoboRealm:
Digital Video Recording system (DVR)
DVR Client-Server presentation
You can use the “DVR Client-server” package as a Video Surveillance System in which parametric data (such as VR_VIDEO_ACTIVITY) from different video cameras will help you search for a video fragment that you are looking for.
You can use the “DVR Client-server” package as a powerful instrument for debugging your video processing and control algorithms that provides access to the values of your algorithm variables that were archived during recording.
Technical Details
- ring video/parametric archive with duration of 1 - 12 months;
- configurable database record (for parametric data) with maximal length of 190 bytes;
- writing of parameters to database with discretization 250 ms;
- the DVR Client can work simultaneously with four databases that can be located at remote computers.
Scorpio presented his great project of the robot "Vanessa" that also used AVM Navigator for space orientation:
Interactive mobile robot “Vanessa”
Simple AVM Navigator tutorial:
Route training and navigation by map
See more details about tuning of “Marker mode” and “Navigation by map” modes.
It’s test of new algorithm for AVM Navigator v0.7.3.
First in video the robot has received command: “go to the checkpoint” and when robot arrived to the checkpoint then I brought robot back (several times) in different position of learned route. When robot noticed the changes then it indicated that robot was displaced because any commands were not given by robot to his motors however changes were seen in the input image.
Then robot started looking around and localized his current position. Further the robot just calculated path from current position to the checkpoint and went there (and so forth).
It is a testing of new robot for AVM Navigator project:
Playing with Twinky rover that was controlled by AVM Navigator:
Object tracking (see here for more detals)
Twinky rover presentation:
https://www.youtube.com/watch?v=xbCpthKrL0o
Looks really promising!
