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action-recognition-visual-attention

Action recognition using soft attention based deep recurrent neural networks

arl_bag2csv

This code is a template for custom rosbag applications and converting rosbags to easy to read .csv files

aruco_hand_eye

Hand-eye calibration integration using aruco_ros and VISP

aruco_hand_eye_cal

aruco_ros

aruco_ros

baxter_skeletonteleop

IK-based teleoperation of Baxter using skeleton data from a depth camera, like Kinect.

birl_tactile_sensor

birl_tactile_sensor

cjson

Ultralightweight JSON parser in ANSI C

convolutional-pose-machine-tf

Convolutional Pose Machine tensorflow implementation

corosensorui

Source Files of CoRo's User Interface

dmp

This ROS package is a general, robot-agnostic implementation of dynamic movement primitives (DMPs).

dmpbbo

C++ library for Function Approximation, Dynamical Movement Primitives, and Black-Box Optimization

easy_handeye

Simple, straighforward ROS library for hand-eye calibration

emg-signal-processing-library

A real-time signal processing library for EMG sensors. View the README.md to see raw vs. processed signals!

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

filterpy

Kalman filtering and optimal estimation library in Python. Kalman filter, Extended Kalman filter, Unscented Kalman filter, g-h, least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

gesture-recognition-for-human-robot-interaction

Gesture Recognition For Human-Robot Interaction with modelling, training, analysing and recognising gestures based on computer vision and machine learning techniques. This work was done at Distributed Artificial Intelligence Lab (DAI Labor), Berlin.

git-base

learning git

gpy

Gaussian processes framework in python

handtracker

3D Hand Tracking using input from a depth sensor.

imu_pipeline

Transforms sensor_msgs/Imu messages into new coordinate frames using tf

ipromplib

ipromp library

ipromps

ipromps

learning_motor_skills_from_partially_observed_movements_executed_at_different_speeds

Here is a code that learns to predict trajectories after training with partially observed movements executed at different speeds. This version uses one single phase parameter.

ml-lib

A machine learning library for Max and Pure Data

moveit

:robot: The MoveIt! motion planning framework

multimodal-prediction-of-intention-with-promps

myo-bluetooth

The BLE specification of the Myo armband

myo-raw

myolinux

C++ library for interfacing with the Myo armband on Linux