Skip to main content

Pathfinding in constrained environments designed for navigating structured networks formed by intersecting circles.

Project description

Overview [DRAFT RELEASE]

This paper introduces an arc-based pathfinding algorithm designed for navigating structured networks formed by intersecting circles, such as biological systems, fiber routing, or mechanical movement constrained to rails. The algorithm leverages geometric relationships and localized search to efficiently compute approximate shortest paths that respect curvature and structural boundaries. Applications include neuron tracing, microfluidic path optimization, vascular modeling, and layout routing for tightly curved circuit or fiber systems.

Usage

coordinates = [[x1,y1],[x2,y2],[x33,y3]]
(shortest_path, walk) = calculate_shortest_path(coordinates)

Introduction

Pathfinding in constrained environments arises in numerous domains, including robotics, biological modeling, and visual story-telling. Classical algorithms perform poorly when paths must conform to geometric constraints such as arcs or structural layouts. This paper introduces an arc-based method that follows the inherent geometric limitations of the domain.

Conclusion

The arc-based pathfinder offers interpretability and structural realism for geometric domains. Future work includes hybridization with linear navigation and deployment in hardware-constrained path systems.

Acknowledgements

We thank the contributors to open-source geometry libraries and acknowledge the support of interdisciplinary visualization research.

REFERENCES

[1] J. A. Reeds and L. A. Shepp. 1990. Optimal paths for a car that goes both forwards and backwards. Pacific J. Math. 145, 2 (1990), 367–393.

Keywords

pathfinding, geometric constraints, KD-tree, circular intersections, robotic navigation, fiber routing

Future Work

  • Extend package to support Z-axis coordinates

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

circlepathfinder-0.0.4.tar.gz (4.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

circlepathfinder-0.0.4-py3-none-any.whl (4.4 kB view details)

Uploaded Python 3

File details

Details for the file circlepathfinder-0.0.4.tar.gz.

File metadata

  • Download URL: circlepathfinder-0.0.4.tar.gz
  • Upload date:
  • Size: 4.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for circlepathfinder-0.0.4.tar.gz
Algorithm Hash digest
SHA256 bdaecee35a855f99ecec46d37348f8cc83e755b76bc2f2ed8086328ea640d681
MD5 b0465856b9b1b6f4329993577c2205ab
BLAKE2b-256 e863023259ec2339e894e71ba628fc709eea632e926ebdf198f9c34980a4e10f

See more details on using hashes here.

Provenance

The following attestation bundles were made for circlepathfinder-0.0.4.tar.gz:

Publisher: workflow.yml on michalkrupa/pathfinding

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file circlepathfinder-0.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for circlepathfinder-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 ef3ac271797078a7e1fd180a4df037d5d1b1066c58901f4691e6717978babce6
MD5 23740ae3b60a29d44597acf449f78cc5
BLAKE2b-256 e961678ba75cf8108c094c099a55ff094e614a5a34cef8c64bc61ee4582007cd

See more details on using hashes here.

Provenance

The following attestation bundles were made for circlepathfinder-0.0.4-py3-none-any.whl:

Publisher: workflow.yml on michalkrupa/pathfinding

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page