Flutter Robot Maps: Rendering Large Occupancy Grids Efficiently

#flutter #robotics #maps #performance

Flutter Robot Maps: Rendering Large Occupancy Grids Efficiently

Robot maps can contain thousands or millions of cells. Building one widget per cell is usually the wrong abstraction; use a rendering strategy that matches scale and update patterns.

Separate map data from UI state

Store dimensions, resolution, origin, and cells in a model. Apply deltas to the model and notify the renderer only when visible regions change.

Choose a rendering strategy

CustomPainter can suit moderate grids with caching and repaint boundaries. Large, frequently changing maps may need tile caching or a native/GPU-backed renderer.

Avoid rebuilding every cell

Batch cells into rows, tiles, or layers. Cache static geometry and invalidate changed regions where supported.

Decouple map and telemetry refresh

Robot pose may update often while occupancy maps change rarely. Render layers at appropriate cadences.

Benchmark zoom and pan

Test representative map sizes, pixel ratios, zooming, and simultaneous telemetry. Track raster time, UI time, and memory.

Example implementation

This Dart snippet illustrates one part of the design. Adapt types, transport behavior, timestamp semantics, and platform APIs to your actual system before production use.

class MapViewportPainter extends CustomPainter {
  MapViewportPainter(this.mapRevision);
  final int mapRevision;

  @override
  void paint(Canvas canvas, Size size) {
    // Draw cached tiles or batched geometry here.
    // Avoid allocating one Paint or widget per occupancy cell.
  }

  @override
  bool shouldRepaint(covariant MapViewportPainter oldDelegate) =>
      oldDelegate.mapRevision != mapRevision;
}

Performance checklist

Measure p95/p99 behavior on target hardware, not only a desktop simulator.
Bound queues and buffers; define what may be coalesced or dropped.
Keep heavy parsing, image processing, and inference away from the Flutter UI thread.
Track source timestamps, sequence numbers, stale-data rate, and dropped updates.
Test network degradation, reconnects, sustained operation, and resource pressure.
Keep control commands and critical alerts separate from replaceable telemetry.