Add KD-tree conflict detection benchmark slice

[ArizmendiWan]

This PR adds a first slice for evaluating faster conflict detection in mapf negotiation by introducing an experimental KD-tree broad phase for proposal conflict checks.

What Changed

• add ConflictDetectionAlgorithm::{Baseline, KdTree} and detect_conflicts_for_proposals(...)
• add a KD-tree broad phase over trajectory bounding-box envelopes before exact conflict checks
• add parity tests to compare baseline vs KD-tree outputs on deterministic synthetic workloads
• add a Criterion benchmark for low/medium/high-overlap synthetic cases
• add a small example that prints baseline-vs-KD-tree comparison stats
• add notes describing the benchmark slice and how to run it

Why

This is meant to test whether a spatial broad phase can reduce candidate pair enumeration before exact conflict checking, especially in sparse workloads, without changing planner semantics.

Verification

Run locally with:

CARGO_HOME=$PWD/.cargo_home cargo test -p mapf
CARGO_HOME=$PWD/.cargo_home cargo run --release -p mapf --example conflict_detection_report
CARGO_HOME=$PWD/.cargo_home cargo bench -p mapf --bench conflict_detection

Observed comparison from the report example:

• low overlap, 64 agents, 32 waypoints: pair enumeration 2016 -> 363
• runtime ~0.51 ms -> ~0.05 ms
• conflict outputs matched the baseline path in the added parity tests

GenAI Use

• I used a GenAI tool in this PR.
• I did not use GenAI
  Generated-by:
  OpenAI Codex (v0.115.0) with GPT-5.4