smolvla-vlabench

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Automate robotic manipulation tasks with Vision-Language-Action policies.

Authorbensonlee5
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides a Vision-Language-Action policy that automates robotic manipulation tasks, enabling precise actions like picking, placing, and grasping objects on a tabletop.

Core Features & Use Cases

  • Vision-Language-Action (VLA) Policies: Utilizes VLA policies for understanding natural language descriptions and performing robotic tasks.
  • Embodied on Franka Panda: Specifically designed to work with the Franka Panda robotic arm.
  • VLABench Integration: Integrated with the VLABench robotic manipulation benchmark for testing and validation.
  • Use Case: Imagine you have a robot that needs to pick up a fruit from a table, place it into a bowl, and then grasp an object. Use this Skill to program the robot's actions using natural language descriptions.

Quick Start

Run the following command to execute the policy: openral benchmark scene --config scenes/benchmark/vlabench_select_fruit.yaml --rskill rskills/smolvla-vlabench

Dependency Matrix

Required Modules

pytorchopenral

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: smolvla-vlabench
Download link: https://github.com/bensonlee5/openral/archive/main.zip#smolvla-vlabench

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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