Mobile Robot Control 2023 Group 5: Difference between revisions
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==Localisation Assignment 1== | ==Localisation Assignment 1== | ||
<br /> | |||
* '''Keep Track of our location''' | * '''Keep Track of our location''' | ||
* '''Observe the Behaviour in Simulation''' | |||
* '''Observe the Behaviour in Reality''' | *'''Observe the Behaviour in Simulation''' | ||
*'''Observe the Behaviour in Reality''' | |||
==Localisation Assignment 2== | ==Localisation Assignment 2== |
Revision as of 15:20, 25 May 2023
Group members:
Name | student ID |
---|---|
Yuzhou Nie | 1863428 |
Ronghui Li | 1707183 |
Guglielmo Morselli | 1959301 |
- Description of the main idea
We choose to implement the Artificial Potential Field (APF) algorithm for obstacle avoidance in robot navigation. It uses laser scanner data to detect obstacles, calculates repulsive forces based on obstacle proximity, converts these forces into velocity commands, and sends these commands to the robot, enabling dynamic navigation.
- Screen recordings of the simulation results
- Video of the robot's performance in real life
Localisation Assignment 1
- Keep Track of our location
- Observe the Behaviour in Simulation
- Observe the Behaviour in Reality