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.