Challenge
Develop a pathfinding system capable of predicting and avoiding potential collisions before they become imminent, while handling growing uncertainty in future states and maintaining efficient routes through real-time risk assessment and adaptive path planning.
Solution
Implemented a novel "probability shadow" system where each agent projects potential future positions as probability distributions, enabling preemptive collision avoidance through shadow intersection analysis and dynamic rerouting when collision risks exceed thresholds.
Implementation
- Developed probabilistic state projection with uncertainty growth
- Created dynamic shadow point generation with confidence scoring
- Implemented real-time collision risk assessment
- Built adaptive rerouting system with timeout mechanisms
- Integrated comprehensive metrics tracking and analytics
- Created sophisticated 3D visualization system
Simulation Analysis
Probability Shadow Avoidance
Visualization of multiple drones using probability shadows for collision prediction and avoidance, showing shadow point distributions and dynamic rerouting based on risk assessment
Shadow Prediction
Accuracy: 96.8%Latency: 14msRisk Assessment
Accuracy: 98.2%Latency: 11msCollision Prevention
Accuracy: 99.4%Latency: 16msTechnical Architecture
Shadow System Architecture
Overview of the probability shadow system components
Shadow Prediction Process
Sequence diagram showing the shadow prediction and risk assessment flow
