py-parry3d
Python bindings for parry3d collision detection, optimized for batch operations with NumPy.
Features
- Batch-first: Process millions of collision queries with minimal Python overhead
- NumPy native: Zero-copy data exchange using contiguous arrays
- Parallel: Automatic multi-threading via Rayon
- Serializable: Cache collision worlds with pre-built BVHs
Installation
pip install py-parry3d
Quick Start
import numpy as np
import py_parry3d as pp
# Define collision shapes
robot_link = pp.CollisionGroup("robot", [pp.Capsule(half_height=0.4, radius=0.08)])
obstacle = pp.CollisionGroup("obstacle", [pp.Box(half_extents=[0.3, 0.3, 0.3])],
static=True, transform=np.eye(4))
# Create world
world = pp.CollisionWorld([robot_link, obstacle])
# Check collisions for 1000 robot poses
N = 1000
# Transforms must be rigid: a proper rotation in the 3x3 block, a
# [0, 0, 0, 1] bottom row, and no NaN/Inf. Anything else raises ValueError.
transforms = {"robot": np.tile(np.eye(4), (N, 1, 1))} # Your actual poses here
pairs = [("robot", "obstacle", 0.0)] # (group_a, group_b, min_distance)
collisions = world.check(transforms, pairs) # (N, 1) bool array
print(f"Collisions: {collisions.sum()} / {N}")
Shapes
# Primitives
pp.Box(half_extents=[0.5, 0.3, 0.2])
pp.Sphere(radius=0.1)
pp.Capsule(half_height=0.5, radius=0.1) # Z-axis aligned
pp.Cylinder(half_height=0.5, radius=0.1) # Z-axis aligned
# Meshes
pp.TriMesh(vertices, faces) # (N,3) float64, (M,3) uint32
pp.TriMesh.from_trimesh(mesh) # From trimesh object
# Convex hull (faster than TriMesh)
pp.ConvexHull_from_trimesh(mesh)
Solid vs Hollow
| Shape | Type | Inside Detection |
|---|---|---|
| Box, Sphere, Capsule, Cylinder, ConvexHull | Solid | Detects objects inside |
| TriMesh | Hollow | Surface contact only |
API
Groups and World
# Dynamic group - transform provided at check time
robot = pp.CollisionGroup("robot", [shape1, shape2])
# Static group - fixed transform
env = pp.CollisionGroup("env", [shape], static=True, transform=tf)
# World
world = pp.CollisionWorld([robot, env])
Transforms
All 4x4 transforms - a CollisionObject local offset, a static group's
transform, and every pose passed to check/check_any - must be rigid:
- the upper-left 3x3 block is a proper rotation (orthonormal, determinant +1); no scale, no shear, no reflection;
- the bottom row is
[0, 0, 0, 1]; - every entry is finite - no
NaN, noInf.
Violations raise ValueError naming the failed check and the offending value.
Orthonormality is checked to a tolerance of 1e-6, far above the float drift of
an accumulated forward-kinematics product (~1e-15) and far below a genuine
error such as a 2x scale.
Collision Checking
# Batch check
result = world.check(transforms, pairs) # (N, n_pairs) bool array
# Early-exit (stops at first collision)
idx = world.check_any(transforms, pairs) # int or None
Pair Helpers
# All pairs between groups
pairs = pp.all_pairs(["l1", "l2", "l3"], skip_adjacent=1)
# Groups vs target
pairs = pp.pairs_vs(["l1", "l2"], "obstacle", min_distance=0.05)
Threading
pp.set_num_threads(8) # Default: all cores
Serialization
data = world.to_bytes()
world = pp.CollisionWorld.from_bytes(data)
# Pickle also supported
Documentation
- DESIGN.md - Architecture and concepts
- EXAMPLES.md - Detailed usage examples
License
MIT
Metadata
Release files for py-parry3d 0.0.3
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