A new advanced example that demonstrates multi-agent trajectory planning using probabilistic inference is now available in the https://examples.rxinfer.com repository.
Example Overview
This example shows how to formulate the problem of coordinating multiple agents navigating through environments with obstacles as a Bayesian inference task. The probabilistic approach enables agents to:
- Navigate effectively through different environment configurations (doorways, walls, combined obstacles)
- Avoid collisions with both static obstacles and other agents
- Generate smooth, efficient trajectories toward goal positions
- Exhibit emergent coordination behaviors without explicit communication
Technical Highlights
The implementation demonstrates several important concepts:
- Encoding collision avoidance as half-space priors
- Modeling agent dynamics with linear state-space equations
- Using message passing for efficient inference
- Visualizing planning results with animated trajectories
Getting Started
You can find the example at Multi-Agent Trajectory Planning · RxInfer.jl Examples. Alternatively you can find this example in the RxInfer.jl documentation under Advanced Examples and many other cool examples. Feel free to experiment with different obstacle configurations, agent parameters, or model variations.
We welcome any feedback or questions about this implementation!