Instuctions on implementing dynamic RRT on Carla simulator
Budget: £36 – £0 GBP
I'm looking for an expert to instruct me in implementing a new variant of the Rapidly-exploring Random Tree (RRT) algorithm on the Carla autonomous driving simulator. The project involves focusing on mixed environments within the simulator with the primary objective being path optimization and dynamic manipulation.
NOTICE: I DON'T NEED YOU TO DO ALL THE WORK FOR ME, I JUST NEED YOU TO PROVIDE ME WITH THE RIGHT GUIDANCE WHEN NECESSARY
Key Requirements:
- Proficient in Python and/or C++ as they are the main languages used in Carla
- Extensive experience with autonomous driving simulators, especially Carla
- Strong background in pathfinding algorithms, particularly RRT
- Previous experience in implementing RRT variants would be preferred
- Ability to analyze and work within mixed environments
Your role will be to guide me through the implementation process, providing insights and expertise as needed. This may involve debugging, and optimizing the dynamic RRT variant for the specific task of path optimization in a variety of mixed environments on the Carla simulator.
NOTICE: I DON'T NEED YOU TO DO ALL THE WORK FOR ME, I JUST NEED YOU TO PROVIDE ME WITH THE RIGHT GUIDANCE WHEN NECESSARY
Key Requirements:
- Proficient in Python and/or C++ as they are the main languages used in Carla
- Extensive experience with autonomous driving simulators, especially Carla
- Strong background in pathfinding algorithms, particularly RRT
- Previous experience in implementing RRT variants would be preferred
- Ability to analyze and work within mixed environments
Your role will be to guide me through the implementation process, providing insights and expertise as needed. This may involve debugging, and optimizing the dynamic RRT variant for the specific task of path optimization in a variety of mixed environments on the Carla simulator.