Implementation of the supervised learning experiments in Vector-based navigation using grid-like representations in artificial agents, as published at https://www.nature.com/articles/s41586-018-0102-6

Torch7 implementation of Grid LSTM as described here: http:https://arxiv.org/pdf/1507.01526v2.pdf

AI-based Modeling and Control of 2-link Robotic Manipulator

ICLR 2023, Spikformer: When Spiking Neural Network Meets Transformer

A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊论文和代码，正在持续更新中。

OpenAI Gym environment solutions using Deep Reinforcement Learning.

Deep Spiking Reinforcement Learning

Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.

칼만 필터는 어렵지 않아(저자 김성필) 파이썬 코드(Unofficial)

Kalman Filter in Python (파이썬으로 구현하는 칼만 필터)

Inverse kinematics estimation of ROBOTIS Open Manipulator X with neural networks

Simulation of spiking neural networks (SNNs) using PyTorch.

Deep learning with spiking neural networks (SNNs) in PyTorch.

High-speed simulator of convolutional spiking neural networks with at most one spike per neuron.

EMG and IMU data recorder GUI for MYO Armband

Python robot's kinematics library

Dynamic Motion Primitives

Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version

Reinforcement learning algorithms for robot control tasks

Example code for using MoveIt with Open Manipulator-X

ROS Noetic package for interacting with the OpenManipulator-X Gazebo simulation

Long short-term memory Spiking Neural Networks

A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.

Deep Q learning algorithm written on PyTorch for solving 2D robot arm reacher

This is the code for the paper Signals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition

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