From Distances to Trajectories: Real-Time Signed Distance Function Mapping and Distance-Accelerated Motion Planning for UAVs
Researchers propose a co-designed system using Signed Distance Functions for real-time mapping and motion planning on autonomous drones.
- New method co-designs mapping and planning using Signed Distance Functions.
- SDFs provide richer obstacle data than binary occupancy maps.
- Enables real-time, onboard trajectory optimization for drones.
- Uses an Octree structure for efficient memory and computation management.
Autonomous flight in cluttered environments requires a robot to build a geometric map and plan safe trajectories simultaneously. Conventional methods often treat mapping and planning as separate stages and rely on binary occupancy maps for collision checking. This approach can limit the efficiency and safety of the resulting paths.
The authors argue for a co-designed system centered around a single representation called a Signed Distance Function. By encoding the exact distance to the nearest obstacle rather than just occupancy status, an SDF provides much richer information for trajectory optimization. This allows the planner to make more informed decisions about safety margins and dynamic feasibility.
The paper develops an Octree-based structure to handle this data efficiently onboard a UAV. This unified framework enables distance-accelerated motion planning, allowing the drone to navigate complex spaces in real time without heavy computational overhead.
Provides a reference architecture for real-time navigation stacks.
Improves viability of autonomous drones in complex industrial settings.
Highlights incremental progress in core robotics infrastructure.
- SDF
- A field that represents the distance of a given point to the nearest surface, with sign indicating inside or outside.
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