Mobile Robot Control 2021 Group 5

Team members

Jaap van der Stoel - 0967407

Roel van Hoof - 1247441

Remco Kuijpers - 1617931 - r.kuijpers1@student.tue.nl - 0611135100

Timo de Groot - 1629352 - t.d.groot2@student.tue.nl

Roy Schepers - 0996153 - r.j.m.schepers@student.tue.nl - 0631329826

Arjan Klinkenberg - 1236143 - a.m.klinkenberg@student.tue.nl

Design document

- The Design Document: File:Design Document Group 5.pdf

Escape Room Challenge

Strategy

At The start of the escape room challange, the PICO searches for the closest wall. It then drives to this wall and allignes itself sideways to the wall. The PICO then drives straight ahead until either another wall, or the exit, is detected. In the first case the PICO rotates to align itself with the new wall and drives forwards again. In the second case the PICO rotates to align with the exit and then drives through the corridor of the finish line. A graphical representation of the strategy can be seen in Figure 1.

Figure 1: The escape room challenge strategy

Implementation

Starting and finding nearest wall

At the start of the run the PICO will turn around 360 degrees to look for the wall which is closest to the PICO. When it has identified this direction it will turn to this direction and drive straight to this wall until it is 0.4m apart from the wall.

Aligning to the walls

As PICO has driven to a wall, it has to align itself to the wall. To do so, laser range finder data is used. The laser range finder should return the same distance at coefficients 0 and 220 for PICO to be alligned to the wall. In Figure 3 it can be seen how the laser range finder coefficients are defined. As previously mentioned, PICO has driven to a nearby wall. Afterwards, it starts rotating quickly until the laser range finder data of coefficients 0 and 220 ratio is less than 0.2. Then it starts rotating slowly, until the laser range finder data of coefficients 0 and 220 ratio is less than 0.04. If this is the case, it is assumed PICO is alligned to the wall.

Figure 3: Illustration of the laser range finder coefficients.

Driving along the wall

Now that PICO has aligned itself to the wall, it is going to drive alongside the wall. By doing so, multiple things can be sensed by the laser range finder. First off, if LRF data [500] senses a wall nearby, PICO stops, turns approximately 90 degrees, aligns itself to the wall, and starts to drive forward again. Secondly, if the ratio between LRF data [0] and [220] becomes too large, it is probable that a gap in the wall PICO is following is found. As a gap is found, PICO stops and is going to execute its exit procedure.

Exiting The Room

When PICO has identified an opening in to a wall it will start the exiting procedure. This will be done by turning around 90 degrees in the direction so that it faces the opening. It then drives sideways up to the point that it is in the middle of the exit corridor. PICO needs to drive forward and checks if it is not going too close to the wall.

Centering in the Halway

For the escape room challenge the decision is made to make the PICO center in the exit hallway. The idea is that this maximizes the distance to the walls and thus minimizes the chances of a collision. In applications where the robot may need to navigate a corridor where other dynamic objects are present, such as humans, it may be desirable to make the PICO drive on one side of the hallway. However, this is not the case for this challenge and thus a more robust solution is better. Centering the PICO in the hallway is accomplished by measuring the distance to the walls at a pre-determined angle to the left and right from the normal direction of the PICO. On each side of the normal 20 datapoints are measured in a band around the set measurement angle α, as shown in the Figure 4. The average of the 20 measured distances is then calculated to mitigate the affect of noise on the measurement. The distance to the left and right are then compared to each other and as long as they are within a certain range the PICO is centered. If they are not within the range the PICO moves either to the right or to the left to compensate. While the PICO is moving left or right it also continues to drive forward, in order to move as fast as possible.

Figure 4: Illustration of the laser range finder coefficients.

Results Escape Room Challenge

The escape room challenge is successfully complete and the PICO has escaped within 42 seconds, as can be seen in the video bellow.

Clip 1: Recording of group 5's performance at the escape room challenge (Sped up 2.75 times.)

Improvements

A few improvements can be considered and may aid in designing better software for the hospital challenge. One possible improvement is to decide, when aligning to the wall, what direction to turn would be the fastest. [add more improvements]

Hospital challenge

Path planning

Artificial potential field Algorithm

Figure 5: Representation on how the robot is attracted by the target and repelled by objects [1]

Robot planning by means of the artificial potential field algorithm acts similarly as a charged particle where the robot is attracted to the target and repelled by obstacles as one can see in Figure 5.

The control input uses the attraction and repulsion factor to calculate the control input and the inputs are the weighted sum of both. These weights can be adapted to the specific needs of the path planning case. One pro of the artificial potential field algorithm is the computational power necessary to plan a path. Additionally, the planned path can be smooth and realistic. However, a con of the artificial potential field algorithm is the possibility to get stuck in a local minimum.

Dijkstra's algorithm

File:Dijkstra Animation The Dijkstra's algorithm is an algorithm for finding the shortest paths between nodes in a graph.

References

[1] = https://sudonull.com/post/62343%E2%80%90What%E2%80%90robotics%E2%80%90can%E2%80%90teach%E2%80%90gaming%E2%80%90AI