Skip to main content

Python bindings for Search-Based Robot Motion Planning (SRMP)

Project description

SRMP is a motion planning software for robotic manipulation, leveraging state-of-the-art search-based algorithms. It ensures consistent and predictable motions, backed by rigorous theoretical guarantees. Additionally, SRMP can efficiently plan for up to dozens of manipulators while guaranteeing collision-free execution—both between robots and with the environment—while maintaining motion consistency and predictability.

Why SRMP?

Existing motion planning frameworks often struggle with the demands of high-stakes applications, where predictability and repeatability are critical. SRMP addresses these challenges by leveraging search-based planning methods, ensuring motions that are both efficient and reliable. Whether you're working on robotic manipulation, industrial automation, or large-scale multi-robot coordination, SRMP provides a powerful solution tailored to your needs.

Key Features

  • Multi-Robot Motion Planning: First-of-its-kind support for planning coordinated motions in multi-manipulator systems.
  • Reliable and Consistent Trajectories: Generates predictable and repeatable motions, making it ideal for high-precision and safety-critical applications.
  • Seamless Integration: Compatible with major simulators, including MuJoCo, Sapien, Genesis, PyBullet and Isaac.
  • Multi-Lingual: Available in both Python and C++ for easy integration into research and industrial workflows.
  • MoveIt! Plugin: Enables deployment on real-world robotic systems with minimal setup.

Getting Started

To get started, check our documentation.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

srmp-0.0.9-cp313-cp313-manylinux_2_35_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.35+ x86-64

srmp-0.0.9-cp312-cp312-manylinux_2_35_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.35+ x86-64

srmp-0.0.9-cp311-cp311-manylinux_2_35_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.35+ x86-64

srmp-0.0.9-cp310-cp310-manylinux_2_35_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.35+ x86-64

srmp-0.0.9-cp39-cp39-manylinux_2_35_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.35+ x86-64

File details

Details for the file srmp-0.0.9-cp313-cp313-manylinux_2_35_x86_64.whl.

File metadata

File hashes

Hashes for srmp-0.0.9-cp313-cp313-manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 b24305cfa893c8f4d402cddaeebe4d9386109ace291cd21494b3522d1d2a0422
MD5 d800e020eb0e4d21ec274f4a01d1c845
BLAKE2b-256 44d7ed49c595732e58965bf76f884a7c19ba99bb921128ce10804bf0c22dde1c

See more details on using hashes here.

File details

Details for the file srmp-0.0.9-cp312-cp312-manylinux_2_35_x86_64.whl.

File metadata

File hashes

Hashes for srmp-0.0.9-cp312-cp312-manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 baad377de507228a01d468ff097c5b48ef5398ce7833a88c58c4280ee9d091a0
MD5 2e694816cd2c07d38adb52e62677f1e8
BLAKE2b-256 8a19b8efe1e2259a67f3462f84a1d3d14b48ac8dad8cdfe560f55de5aa677a7d

See more details on using hashes here.

File details

Details for the file srmp-0.0.9-cp311-cp311-manylinux_2_35_x86_64.whl.

File metadata

File hashes

Hashes for srmp-0.0.9-cp311-cp311-manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 bffc7928487b1777055ce98e64bbabf442e4ee087cbf3c815c90c31daf10e7c8
MD5 a785775ada34e3460c1438fe4bf0dd75
BLAKE2b-256 9d3e85a00bc8e83cb5ae677385660ed663776dd1c72b4bc11a2c6592cb9f5bd4

See more details on using hashes here.

File details

Details for the file srmp-0.0.9-cp310-cp310-manylinux_2_35_x86_64.whl.

File metadata

File hashes

Hashes for srmp-0.0.9-cp310-cp310-manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 7229968e6077dc84ea95de7c20bca9a2e48b3c7af8143b41432125d994f6b5ac
MD5 05175a0a0c56d1cf405841e78433161f
BLAKE2b-256 a2e3eddac24ebfdc1628e54ae955327fcab92a4abd04d0c55868db2fea2e2326

See more details on using hashes here.

File details

Details for the file srmp-0.0.9-cp39-cp39-manylinux_2_35_x86_64.whl.

File metadata

  • Download URL: srmp-0.0.9-cp39-cp39-manylinux_2_35_x86_64.whl
  • Upload date:
  • Size: 9.6 MB
  • Tags: CPython 3.9, manylinux: glibc 2.35+ x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for srmp-0.0.9-cp39-cp39-manylinux_2_35_x86_64.whl
Algorithm Hash digest
SHA256 25dd7f3fa07d53f9d66eb35bfda2130bd1f87c1bf4658d93e170772945c00801
MD5 41389cdb84923332ea0d5b9c37690b58
BLAKE2b-256 aa547c40621c2bcb5f75ead995fcfbd8ae78edc532093ca207f25127ede5b16f

See more details on using hashes here.

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