Autonomous robot's navigation

Since October 2007 I developed new object recognition algorithm “Associative Video Memory” (AVM).

A?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.

A?And now I want to introduce my experiment with robot navigation based on visual landmark beacons: “Follow me” and “Walking by gates”.


Follow Me


Walking from p2 to p1 and back

I embodied both algorithms to Navigator plugin for using within RoboRealm software.
A?So, you can try now to review my experiments with using AVM Navigator.

The Navigator module has two base algorithms:

-= Follow me =-
A?The navigation algorithm do attempts to align position of a tower and the body
A?of robot on the center of the first recognized object in the list of tracking
A?and if the object is far will come nearer and if it is too close it will be
A?rolled away back.

-= Walking by gates =-
A?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
    A?For training of the route you have to indicate actual route (button “Walking by way”)
    A?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.

A?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.

A?If robot can’t recognize anything (gate/object) then robot will be turning around on the spot
A?for searching (it may twitch from time to time in a random way).

A?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 Odometry Test


Navigation by map


Visual Landmark Navigation

I have done new plugin for RoboRealm:



Digital Video Recording system (DVR)

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.

I prepared simple video tutorial “Route training and navigation by map”:



See more details about tuning of “Marker mode” and “Navigation by map” modes.

http://edv-detail.narod.ru/trend_empty_cells.png

http://edv-detail.narod.ru/dvr_client_trend_2.png

AVM Navigator v0.7.4.2 update

Changes:

- The indication drawing was carried to ::Annotate method



- Into camera view was added 3D marker of target position of robot



See here about all other changes.

Fun with AVM Navigator



It’s little demo of object recognition and learning from motion with helping of AVM Navigator.

All object rectangle coordinates are available in RoboRealm pipeline from external variables:
NV_ARR_OBJ_RECT_X - left-top corner X coordinate of recognized object
NV_ARR_OBJ_RECT_Y - left-top corner Y coordinate of recognized object
NV_ARR_OBJ_RECT_W - width of recognized object
NV_ARR_OBJ_RECT_H - height of recognized object

So you can use it in your VBScript program.

See here for more details.

In fact the AVM algorithm is not invariance to rotation and you should show the object for memorizing to AVM search tree under different angles during training for further correct recognition.

See also an example of using of Canny module as background for AVM Navigator:

Hi guys,

I’m still working over AVM technology. Now I’ve founded my own company that is named Invarivision.com.
We are small but passionate team of developers that are working over system which would be able watch TV and recognize video that interests user.

And we need your help!

It seems that interface of our search system is good enough because we try to make it to be simple and user friendly but from other point of view it could be a total disaster.

Could you please take a look to our system and then tell us about good and bad sides of this?

The constructive criticism is welcome.

With kind regards, EDV.