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use crate::math::{Isometry, Vector};
use crate::query::algorithms::VoronoiSimplex;
use crate::query::algorithms::{gjk, gjk::GJKResult, CSOPoint};
use crate::query::ClosestPoints;
use crate::shape::SupportMap;
use na::{RealField, Unit};

/// Closest points between support-mapped shapes (`Cuboid`, `ConvexHull`, etc.)
pub fn closest_points_support_map_support_map<N, G1: ?Sized, G2: ?Sized>(
    m1: &Isometry<N>,
    g1: &G1,
    m2: &Isometry<N>,
    g2: &G2,
    prediction: N,
) -> ClosestPoints<N>
where
    N: RealField,
    G1: SupportMap<N>,
    G2: SupportMap<N>,
{
    match closest_points_support_map_support_map_with_params(
        m1,
        g1,
        m2,
        g2,
        prediction,
        &mut VoronoiSimplex::new(),
        None,
    ) {
        GJKResult::ClosestPoints(pt1, pt2, _) => ClosestPoints::WithinMargin(pt1, pt2),
        GJKResult::NoIntersection(_) => ClosestPoints::Disjoint,
        GJKResult::Intersection => ClosestPoints::Intersecting,
        GJKResult::Proximity(_) => unreachable!(),
    }
}

/// Closest points between support-mapped shapes (`Cuboid`, `ConvexHull`, etc.)
///
/// This allows a more fine grained control other the underlying GJK algorigtm.
pub fn closest_points_support_map_support_map_with_params<N, G1: ?Sized, G2: ?Sized>(
    m1: &Isometry<N>,
    g1: &G1,
    m2: &Isometry<N>,
    g2: &G2,
    prediction: N,
    simplex: &mut VoronoiSimplex<N>,
    init_dir: Option<Vector<N>>,
) -> GJKResult<N>
where
    N: RealField,
    G1: SupportMap<N>,
    G2: SupportMap<N>,
{
    let dir = match init_dir {
        // FIXME: or m2.translation - m1.translation ?
        None => m1.translation.vector - m2.translation.vector,
        Some(dir) => dir,
    };

    if let Some(dir) = Unit::try_new(dir, N::default_epsilon()) {
        simplex.reset(CSOPoint::from_shapes(m1, g1, m2, g2, &dir));
    } else {
        simplex.reset(CSOPoint::from_shapes(m1, g1, m2, g2, &Vector::x_axis()));
    }

    gjk::closest_points(m1, g1, m2, g2, prediction, true, simplex)
}