Mobile Robot Control 2023 The Iron Giant

Group members:

Name	student ID
Tobias Berg	1607359
Guido Wolfs	1439537
Tim de Keijzer	1422987
Marijn van Noije	1436546
Tim van Meijel	1415352
Xander de Rijk	1364618
Stern Eichperger	1281232

The midterm presentation of The Iron Giant: File:Midterm-presentation-The-Iron-Giant.pdf

The feedback and questions received regarding the midterm presentation of The Iron Giant are as follows:

Feedback point 1:

• The current state diagram does not include a recovery state to resolve a deadlock situation. If a passage suddenly becomes blocked and remains blocked, the robot could potentially end up in a deadlock. This could occur, for example, if a person obstructs a pathway between obstacles and does not move away.

Solution: To address this issue, an additional recovery loop should be added for handling suddenly blocked pathways. In this loop, the obstructing obstacle is added to the map, and a alternative new path is calculated using the A* algorithm.

Question 1:

• How does the robot transition into the pose recovery state? What parameter or condition is used?

Solution/answer: A condition based on the standard deviation of the particle spread should be implemented. If the deviation is too large, indicating a significant spread of particles and therefore an uncertain estimation, the robot has lost knowledge of its position in the world and needs to recover it.

Question 2:

• Why was the "happy flow" defined in this manner? Won't the robot always encounter disturbances and dynamic objects that cause it to loop through parts of both the happy and unhappy flows? In such cases, the loop may not necessarily be considered an unhappy flow.

Solution/answer: It is true that the definition of the happy flow was somewhat rigid. It is true that certain segments of the "unhappy flow" may occur within the expected states the robot will loop trough during the challenge. This does not pose a problem and does not represent an unhappy flow.

Figure 1. Updated state diagram after design presentation.

We updated the state diagram according to the feedback and questions as shown in Figure 1.

Introduction

Intro hoe we onze robot willen programeren

Strategy description Hoe willen we het gaan bereiken

Algorithms used, software Architecture

A star

Particle filter

Artificial potential field algorithm

How are the algoritms connected to each other

How was the performance verified

Robustness

Conclusion

Wat hebben we bereikt

Discussion

Discusseer wat verbeterd kan worden

Future steps

Expliciet beschrijven wat de volgende stappen zijn