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Found 10 papers, 1 papers with code
A Q-learning approach to the continuous control problem of robot inverted pendulum balancing
This study evaluates the application of a discrete action space reinforcement learning method (Q-learning) to the continuous control problem of robot inverted pendulum balancing.
A study on a Q-Learning algorithm application to a manufacturing assembly problem
This study focuses on the implementation of a reinforcement learning algorithm in an assembly problem of a given object, aiming to identify the effectiveness of the proposed approach in the optimisation of the assembly process time.
Event-based tracking of human hands
Tracking of human hands in 3D space using a single event camera data and lightweight algorithms to define ROI features (hands tracking in space).
Improving novelty detection with generative adversarial networks on hand gesture data
Nevertheless, a novelty detection accuracy of 95. 4% or 90. 2% (depending on the data set) was achieved with just 5% loss of accuracy on trained classes.
Deep reinforcement learning applied to an assembly sequence planning problem with user preferences
The results support the potential for the application of deep reinforcement learning in assembly sequence planning problems with human interaction.
Classification of Primitive Manufacturing Tasks from Filtered Event Data
Several filters are compared and combined to remove event data noise.
Gesture Recognition from Skeleton Data for Intuitive Human-Machine Interaction
We propose an approach for segmentation and classification of dynamic gestures based on a set of handcrafted features, which are drawn from the skeleton data provided by the Kinect sensor.
KUKA Sunrise Toolbox: Interfacing Collaborative Robots with MATLAB
Collaborative robots are increasingly present in our lives.
Robotics
High-level programming and control for industrial robotics: using a hand-held accelerometer-based input device for gesture and posture recognition
The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high-level of abstraction from the robot language.
Robotics
Real-Time and Continuous Hand Gesture Spotting: an Approach Based on Artificial Neural Networks
New and more natural human-robot interfaces are of crucial interest to the evolution of robotics.
