Archives for posts with tag: Killough

Hi,

Yesterday I published building instructions for a single leg of my holonomic robot Agilis. Here are the full instructions. These include the central frame and three sensor docks. Have fun with it.

Download the Building instructions

Agilis2

Agilis2WithBrick

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I got some feed-back on my last post with “building instructions” for Agilis. My friend Kirk wondered why I didn’t make proper instructions. He was not impressed by my lame excuses about odd angles or illegal builds and showed me things could be done. He was right, it was about time for me to master some Lego CAD tools. I choose to use LDraw¬†and MLCad for the job. My fears for a steep learning curve proved wrong. The manual is quite good and I was up and running within an hour. The hardest thing to learn was the discipline to work precise immediately. One cannot build a sketch at first and then improve the model. Well, technically you can, but you shouldn’t as every brick you move triggers a chain of new moves that need to be made.

AgilisFront
It was fun to create proper building instructions for Agilis. Along the way I also improved the gearbox as was suggested by another reader of my blog, Thimoty. You can freely download the instructions. I do appreciate constructive feedback. This is my first and I am sure there is room for improvement.

Download the building instructions for Agilis

This time I want to introduce you to Koios the guard bot. Koios guards my house, it detects intruders and scares them away.

To perform this complicated task I have split Koios’ behavior into different subtasks and put these in a subsumption architecture.

The first task of Koios is to map its surrounding using two range sensors. These are an ultrasonic sensor for long range (<200 cm) and a Mindsensors dist sensor for accuracy on the short range (<80 cm). To map the surrounding Koios makes a full turn in place while scanning. The resulting map is what I call a circular range map. This means that the map stores the distance to the nearest obstacle for all directions (I recognize 24 directions, each 15 degrees wide). The map looks like a radar scan when plotted. This map is not permanent, it will be thrown away when Koios moves. As Koios does not try to build and maintain a more permanent map of its surrounding I did not have to deal with uncertainties about its absolute position. Therefore the mapping algorithm could be kept simple.

The second task of Koios is to find a safe spot on the map and then to move to this spot. A safe spot for Koios is a spot where Koios is surrounded by objects. A place next to a wall is good, a place in a corner is better. Koios finds a safe spot by examining the map for a place between obstacles. When the safest spot on the map is found Koios travels to this place in a straight line.
Once arrived at the new location Koios again makes a map of the surrounding. If, at second glance, the current location is safe enough then Koios will stay there. If not, it will try to find an even safer spot. This process is repeated until a location is found that is safe enough for Koios.
The video below shows Koios scanning the area and finding a safe spot. I actually had some trouble shooting the video. At first I had placed my webcam on a chair to shoot the video. But to my surprise Koios hid itself under the chair. This indeed is a very safe spot, but it was outside the frame of the video. In the end I placed the camero on my desk to shoot the clip.

When Koios has found a really safe spot it will start guarding the area. It will slowly turn in place while scanning the area again. If an obstacle is detected its location will be compared to the map. When the obstacle is already on the map it will be regarded as a part of the surrounding and ignored. If on the other hand it isn’t on the map then it must be something new and it will be treated as an intruder.
The task of guarding is rather complicated as there is always some uncertainty in both the map and the range sensor data. Suppose the map tells Koios that there is an obstacle at 150 cm and the range sensor detects an object at 145. Is this an intruder or part of the surrounding? The choice Koios makes is based on statistics. To support this kind of decision making a range map stores more information than just the range to the nearest object. It also stores statistical quantities like the number of measurements taken at the direction and the variance in measured ranges. This makes it possible to calculate the probability of an obstacle being new, an intruder, or old, part of the surrounding. If part of the surrounding the measurement is used to improve the map even further.

But if the object is an intruder Koios will home in on it! Koios will quickly run to the intruder until it is very close. I haven’t written this part of Koios’ behavior yet. So everything you read from now on is just on the drawing board.
For one thing I have not decided yet if Koios just runs blindly to the location where the intruder was detected or that it tries to maintain a lock on the intruder while homing in on it. It would be nice if Koios was able to maintain a lock. But it will also be complicated. Mayby I could use a heat sensor like some air-to-air missiles do to maintain a lock on the intruder.

Anyway, once close to the intruder Koios will scare it away using both light and sound. First it will mimic some kind of scary animal with eyes that glow in the dark while making scary noises. Then it will mimic the police using flash lights and and a siren. Then it will map its surrounding again to find a save spot and make a hasty retreat.

For my birthday I got the Rotacaster wheels, four of them!


They are nice! A bit smaller than I expected, but the size is perfect. It gave me some new challenges. I never built a triangular robot before.
Below are the first picturesof my triangular robot. For prototype I’m rather pleased with it, it is compact, lightweight and sturdy. The only real issue with the robot is that I cannot replace the batteries without removing the NXT from the chassis.

The robot features a US-sensor, giving it a face and a front side, a Mindsensors medium range distance sensor, a Hitechnic gyro sensor and a Mindsensors accelerometer. There is a Mindsensors sensor port splitter on the bottom of the robot that it is out of view. Currently only the gyro is functional, it helps the robot to keep its orientation.

There is not much programming done yet. The only new stuff I wrote thus far deals with driving. The robot can drive in any direction. It can spin around its vertical axis and it can orientate itself in a certain direction. It can do all off this at the same time. It is really funny to look at the robot performing some of the patterns that I used for testing.
I’m not sure what kind of behaviour I will give this robot. My son wants to control it with a joystick. So that might be the first thing to implement.

The robot does not have a name yet. Any suggestions?