Analysis in docs/brouter-findings.md: how BRouter knows roads (.rd5 segments), routes and reaches low elevation gain (profile uphill/downhill cost + kinematics), the three call surfaces, and an evaluation of two ideas — fill GPS gaps along roads, and offline waypoint route planning. License is MIT; the engine has no desktop-only deps, so it embeds on Android ART. Stage 1 (embed + bridge, compiles into the apk; on-device route not yet run): - vendored brouter-1.6.3-all.jar into the Android module (dexes cleanly) and bundled the trekking/shortest profiles + lookups.dat as assets, copied to files/brouter/profiles2 on launch - MainActivity: a brouter_command.txt handler on the existing FileObserver runs btools.router.RoutingEngine off the UI thread (recipe taken via javap from ServerHandler) and returns the track as GPX - Rust brouter_route command: same file bridge as GPS (request + command, poll for the result), registered in the invoke handler - frontend/js/router.js: BRouter.route(points, profile) -> GPX (parseRouteGPX) - LICENSE-brouter (MIT notice) kept alongside the vendored engine Segments (.rd5, ~13-23 MB per 5x5 tile) are delivered later (Stage 2, wired download inside BalDav). IMPLEMENTATION_PLAN.md tracks the 5 stages. |
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| .. | ||
| bmr.js | ||
| chzn.js | ||
| db.js | ||
| gps.js | ||
| main.js | ||
| router.js | ||
| tilecache.js | ||