Mobile Robot Control 2024 HAL-9000
Group members:
| Name | student ID |
|---|---|
| Salim Achaoui | 1502670 |
| Luis Ponce Pacheco | 2109417 |
| Nienke van Hemmen | 1459570 |
| Mohamed Elbehery | 1035058 |
| Aniek Wigman | 1463535 |
| Max Hage | 1246704 |
| Max van der Donk | 1241769 |
Exercise 1: Non-crashing robot
For the first exercise, the goal was to ensure that the robot does not move through walls in the simulation and not crash into the walls in both the simulation and the real world. To solve this matter, there were multiple solutions. The first solution collects all of the data from the lasers and stops the robot when it reaches a wall. A second solution also uses this notion but instead of stopping the robot, the robot turns away from the wall. These solutions were then tested on the robot in real life. After testing, it became clear that, although stopping the robot was not an issue, the robot was not able to move along a wall in parallel. This issue occurred since the sensor data was taken uniformly. So on all sides, the robot would stop with the same threshold. Therefore, a third solution was made that took the orientation of the sensor data into account for the robot to move alongside a wall. The details of the solutions will now be covered in more detail.
Solution 1
For the first solution, we utilize the laser data that the robot has. This contains data as to how far a wall or object is to the robot at a certain angle. For each angle, we check whether the robot is too close to an obstacle, thus within range x. If it is, it stops moving. Else, it keeps on going forward.
Solution 2
For the second solution, the first solution was expanded. Instead of just stopping, the robot now rotates until no obstacle is close to the robot anymore, and it moves forward again.
Solution 3
This solution is also an expansion of solution 1. In this expansion, the size of the robot is taken into account aswell. This solution was created after testing the robot physically. We came to the realisation that the size of the robot is not taken into account. Therefore, in the script an offset was included such that the body of the robot does not bump into the wall. using the line: scan.ranges[i] < minDist + robotWidth*abs(sin(currentAngle) we introduce an offset by adding the sinusoid of the current angle, which is approximately the circular body of the robot. Because the laser of the robot is approximately in the middle of its body, the sinusoid creates a proper offset to not bump into a wall anymore.
For local navigation, 2 different solutions had to be introduced for the restaurant scenario. We have chosen for artificial potential fields and vector field histograms because these solutions seemed the most robust to us. In this parahraph the 2 solutions will be explained.
Artificial potential fields
Vector field histogram
*insert explanation for how this method works*
for vector field histograms, 2 major components had to be created. Firstly, the translation from the laser data to a map that contains the coordinates of the obstacles together with a certainty value and a polar histogram, from which a minima should be chosen as direction to continue moving.