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Tags: Hardware and IoT

1.stack-of-tasks / pinocchio

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

robotics
dynamics
analytical-derivatives
kinematics
c-plus-plus
rigid-body-dynamics
+11 more

C++BSD-2-CLAUSE3.8K total593 forks

+67 stars

from 3,771 · score 4.22

2.ethz-adrl / control-toolbox

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

optimal-control
model-predictive-control
ilqr
ilqg
robotics
trajectory-optimization
+9 more

C++BSD-2-CLAUSE1.7K total343 forks

+11 stars

from 1,711 · score 2.48

3.MIT-SPARK / Kimera

Index repo for Kimera code

robotics
computer-vision
semantics
3d-reconstruction
slam
visual-inertial-odometry

BSD-2-CLAUSE2.1K total240 forks

+10 stars

from 2,133 · score 2.40

4.koide3 / hdl_graph_slam

3D LIDAR-based Graph SLAM

ros
slam
lidar
velodyne
hdl-graph-slam
point-cloud
+1 more

C++BSD-2-CLAUSE2.3K total748 forks

+7 stars

from 2,336 · score 2.08

5.atenpas / gpd

Detect 6-DOF grasp poses in point clouds

grasping
robotics
ros

C++BSD-2-CLAUSE768 total248 forks

+3 stars

from 765 · score 1.39

6.MIT-SPARK / Kimera-Semantics

Real-Time 3D Semantic Reconstruction from 2D data

semantic-segmentation
volumetric-reconstruction
3d-reconstruction
robotics
mapping
reconstruction
+7 more

C++BSD-2-CLAUSE756 total146 forks

+3 stars

from 753 · score 1.39

7.srl-freiburg / pedsim_ros

Pedestrian simulator powered by the social force model

ros
social-force-model
crowd
pedsim
pedestrian
simulation-environment
+1 more

C++BSD-2-CLAUSE593 total170 forks

+3 stars

from 590 · score 1.39

8.koide3 / ndt_omp

Multi-threaded and SSE friendly NDT algorithm

ros
pcl
ndt-algorithm
multithreading
registration
point-cloud
+3 more

C++BSD-2-CLAUSE861 total385 forks

+2 stars

from 859 · score 1.10

9.antirez / micropython-telegram-bot

MicroPython telegram bot library: simple way to put your IoT projects on the cloud

Python BSD-2-CLAUSE65 total7 forks

+1 stars

from 64 · score 0.69

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before the first daily record that AwesomeRepos made for the repository. A longer window needs more of these daily records first. A repository younger than the window does not rank in it.

The filters select from the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it. See Tags.

A new repository enters the index when it gains stars faster than the published admission threshold, whatever its size. A repository stays in the index after it enters. Thus an archived repository can still rank.

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