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rl robotic grasping a2c a3c · fmarcantoni

Reinforcement learning implementations including vision-based robotic grasping in PyBullet.

a2ca3cactor-critic-modelpolicy-gradientspybullet
Publisher repository ↗
rl robotic grasping a2c a3c · fmarcantoni resource page screenshot
Resource screenshot · captured 2026-10-08 · visually reviewed

Overview

Reinforcement learning implementations including vision-based robotic grasping in PyBullet.

Publisher summary: “Policy iteration, REINFORCE, A2C, and A3C for decision-making, LunarLander control, and vision-based robotic grasping in PyBullet.”

Use its repository to inspect the implementation, documentation and supported workflows. This directory record identifies the maintainer, code license and related resources; it does not claim that the project has been installed or tested on your robot.

Project information

Maintainer
fmarcantoni
Primary language
Python
Repository code license
Not specified
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2026-05-13

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • RBE 577 Project 3: Reinforcement Learning Agents for Lunar Lander and KUKA
  • Overview
  • A2C Subproject
  • Overview
  • Key Features
  • Code Structure

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