Add VFH Step 1: polar histogram construction from LiDAR data

[Khushi0512]

Implements the first incremental step of the Vector Field Histogram (VFH) roadmap agreed with the maintainer in issue #52: build a 1D polar obstacle density histogram around the vehicle directly from the existing 2D LiDAR sensor simulation, with configurable sector resolution and smoothing.

• PolarHistogram (src/components/mapping/polar_histogram/polar_histogram.py): pure-logic histogram construction. Bins LiDAR returns into angular sectors, weights each by the classic VFH linear magnitude falloff (Borenstein & Koren, 1991), and applies a triangular smoothing filter across neighboring sectors.
• PolarHistogramMapper (polar_histogram_mapper.py): wires PolarHistogram to the existing OmniDirectionalLidar point cloud and renders it as a ring of colored wedges around the vehicle (denser sectors longer/redder), using the project's existing mapper slot on FourWheelsVehicle - mirrors PotentialFieldMapper's update(point_cloud, state) / draw(axes, elems) interface, so no changes were needed to shared vehicle/visualizer code.
• vfh_polar_histogram_construction.py: simulation entry point, reusing the same obstacle scenario as the existing lidar_obstacle_sensing sample so the histogram's behavior can be compared directly against the raw point cloud it's built from.
• Unit tests for histogram binning/smoothing math, the mapper, and the simulation entry point (15 tests total).
• Regenerated pyrightconfig.json / devcontainer.json extraPaths via generate_pyrightconfig.py for the two new module directories.

Valley/direction selection is intentionally left for Step 2 per the agreed roadmap, to keep this PR small and reviewable.

How it was verified: all 15 new tests pass via pytest (matching the project's existing show_plot=False test convention), and the full simulation runs cleanly end to end.