Mobile Robot Control 2023 The Iron Giant: Difference between revisions
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The midterm presentation of The Iron Giant: | The midterm presentation of The Iron Giant: | ||
[[File:Midterm-presentation-The-Iron-Giant.pdf|thumb]]The feedback and questions received regarding the midterm presentation of The Iron Giant are as follows: | [[File:Midterm-presentation-The-Iron-Giant.pdf|thumb]] | ||
The feedback and questions received regarding the midterm presentation of The Iron Giant are as follows: | |||
'''Feedback point 1:''' | '''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. | *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.'' | ''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.'' | ||
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'''Question 1:''' | '''Question 1:''' | ||
* How does the robot transition into the pose recovery state? What parameter or condition is used? | *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.'' | ''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.'' | ||
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'''Question 2:''' | '''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. | *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.'' | ''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.'' | ||
<br /> | <br /> | ||
[[File:State diagram update.jpeg|thumb | [[File:State diagram update.jpeg|thumb|Figure 1. Updated state diagram after design presentation.]] | ||
We updated the state diagram according to the feedback and questions as shown in Figure 1. | We updated the state diagram according to the feedback and questions as shown in Figure 1. | ||
Revision as of 13:59, 8 June 2023
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.
We updated the state diagram according to the feedback and questions as shown in Figure 1.