Mobile Robot Control 2023 Group 15
Group members:
| Name | student ID |
|---|---|
| Tobias Berg | 1607359 |
| Guido Wolfs | 1439537 |
| Tim de Keijzer | 1422987 |
Practical exercises week 1:
1. On the robot-laptop open rviz. Observe the laser data. How much noise is there on the laser? What objects can be seen by the laser? Which objects cannot? How do your own legs look like to the robot.
The laser data shows with point clouds highlighted in red where objects are. In a constant environment the laser data is still quite fluid and dynamic. This indicates that there is significant noise on the robot. As of our own legs, they are visible as two small rectangles.
2. Go to your folder on the robot and pull your software.
This has been done.
3. Take your example of don't crash and test it on the robot. Does it work like in simulation?
After significant tweaking and updates, yes the simulation works.
4. Take a video of the working robot and post it on your wiki.
Video below:
Practical exercises week 2:
To improve the efficiency of finding the shortest path through the maze, it is suggested to decrease the number of nodes. By reducing the number of nodes, the algorithm will have to evaluate fewer nodes, which will make it more efficient.
The number of nodes can be reduced by removing nodes that are between the nodes that represent a straight line in the maze, as illustrated in Figure 1. This method results in a maze with 19 nodes, and the connections between them are indicated by red dotted lines. It is important to note that the cost of the straight paths should be updated to match the original cost of the same path. For example, the path between node 1 and 2 in the maze of Figure 1 would have a cost of 6.