wire repository

Repository Summary

Checkout URI https://github.com/tue-robotics/wire.git
VCS Type git
VCS Version melodic-devel
Last Updated 2020-06-30
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Package Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
armadillo_matrix 0.0.1
problib 0.0.1
wire 0.0.1
wire_core 0.0.1
wire_msgs 0.0.1
wire_state_estimators 0.0.1
wire_tutorials 0.0.0
wire_viz 0.0.1

README

wire

Introduction

Wire generates and maintains one consistent world state estimate based on object detections. It solves the data association problem by maintaining multiple hypotheses and facilitates tracking of various object attributes. The state estimators used for estimation and the probabilistic models used for association can be configured. Technical details can be found in this paper:

J. Elfring, S. van den Dries, M.J.G. van de Molengraft, M. Steinbuch, Semantic world modeling using probabilistic multiple hypothesis anchoring, Robotics and Autonomous Systems, Volume 61, Issue 2, February 2013, Pages 95-105, (pdf) which also includes a more detailed explanation of the algorithm.

Wire introdcution video

Tutorials

Tutorials can be found on the ROS wiki.

CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/tue-robotics/wire.git
VCS Type git
VCS Version master
Last Updated 2020-08-01
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Package Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
armadillo_matrix 0.0.1
problib 0.0.1
wire 0.0.1
wire_core 0.0.1
wire_msgs 0.0.1
wire_state_estimators 0.0.1
wire_tutorials 0.0.0
wire_viz 0.0.1

README

wire

Introduction

Wire generates and maintains one consistent world state estimate based on object detections. It solves the data association problem by maintaining multiple hypotheses and facilitates tracking of various object attributes. The state estimators used for estimation and the probabilistic models used for association can be configured. Technical details can be found in this paper:

J. Elfring, S. van den Dries, M.J.G. van de Molengraft, M. Steinbuch, Semantic world modeling using probabilistic multiple hypothesis anchoring, Robotics and Autonomous Systems, Volume 61, Issue 2, February 2013, Pages 95-105, (pdf) which also includes a more detailed explanation of the algorithm.

Wire introdcution video

Tutorials

Tutorials can be found on the ROS wiki.

CONTRIBUTING

No CONTRIBUTING.md found.