Webots youBot Navigation Algorithms
Budget: $30 – $250 USD
I am developing a cognitive-robotics project in Webots centred on the KUKA youBot. At this stage I need the navigation layer built out so the robot can autonomously:
• generate a collision-free path through a known or partially known workspace,
• detect and avoid static as well as moving obstacles in real time, and
• keep an accurate estimate of its pose throughout the run.
You are free to use the Webots API in C++ or Python, and ROS 2 integration is welcome if it speeds up localisation or leverages existing SLAM libraries. All code has to compile and run inside the latest public Webots release; please include any additional package dependencies in a requirements file so the controller remains fully reproducible.
Deliverables
1. Source code for path-planning, obstacle-avoidance and localisation modules, wired into a single controller.
2. A Webots world (or worlds) that demonstrates the above capabilities.
3. A concise README explaining how to build, launch and test the solution, plus notes on extending it to perception and pick-and-place in future phases.
4. Short video or GIF capture showing the robot completing at least one start-to-goal mission without operator intervention.
To be considered, attach a detailed project proposal that outlines the algorithmic approach, milestones, and estimated completion times.
• generate a collision-free path through a known or partially known workspace,
• detect and avoid static as well as moving obstacles in real time, and
• keep an accurate estimate of its pose throughout the run.
You are free to use the Webots API in C++ or Python, and ROS 2 integration is welcome if it speeds up localisation or leverages existing SLAM libraries. All code has to compile and run inside the latest public Webots release; please include any additional package dependencies in a requirements file so the controller remains fully reproducible.
Deliverables
1. Source code for path-planning, obstacle-avoidance and localisation modules, wired into a single controller.
2. A Webots world (or worlds) that demonstrates the above capabilities.
3. A concise README explaining how to build, launch and test the solution, plus notes on extending it to perception and pick-and-place in future phases.
4. Short video or GIF capture showing the robot completing at least one start-to-goal mission without operator intervention.
To be considered, attach a detailed project proposal that outlines the algorithmic approach, milestones, and estimated completion times.
Related categories:
C Programming
Python
CUDA
C++ Programming
Robotics
AI Model Development
AI Research
AI Development