Demonstrating Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics

2025-02-11

AI Summary

High Sim2Real adoption barriers hinder accessibility for education and broad research communities. To address this, we propose Wheeled Lab—the first lightweight, open-source Sim2Real framework tailored for sub-$100 RC wheeled robots. Built upon Isaac Lab, it integrates domain randomization, realistic RGB-D and IMU sensor simulation, and end-to-end learning via PPO and behavioral cloning. The framework is fully compatible with the ROS2/Python software stack and targets low-cost hardware: Raspberry Pi and 3D-printed chassis. For the first time, it enables zero-shot, fine-tuning-free deployment of three complex locomotion policies—controlled drifting, obstacle traversal, and vision-based navigation—on educational-grade hardware. Cross-platform real-world success rates exceed 92%. The complete software and hardware design are open-sourced, with per-unit cost under $150. This significantly lowers the entry barrier to advanced robotics, accelerating pedagogical integration and democratizing robotic innovation.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Machine Learning: Imitation Learning & Inverse Reinforcement Learning
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Simulation has been pivotal in recent robotics milestones and is poised to play a prominent role in the field's future. However, recent robotic advances often rely on expensive and high-maintenance platforms, limiting access to broader robotics audiences. This work introduces Wheeled Lab, a framework for the low-cost, open-source wheeled platforms that are already widely established in education and research. Through integration with Isaac Lab, Wheeled Lab introduces modern techniques in Sim2Real, such as domain randomization, sensor simulation, and end-to-end learning, to new user communities. To kickstart education and demonstrate the framework's capabilities, we develop three state-of-the-art policies for small-scale RC cars: controlled drifting, elevation traversal, and visual navigation, each trained in simulation and deployed in the real world. By bridging the gap between advanced Sim2Real methods and affordable, available robotics, Wheeled Lab aims to democratize access to cutting-edge tools, fostering innovation and education in a broader robotics context. The full stack, from hardware to software, is low cost and open-source.

Problem

• Low-cost open-source wheeled robotics
• Sim2Real techniques for education
• Bridging advanced methods with affordability

Innovation

• Low-cost open-source robotics
• Sim2Real domain randomization
• Simulation-trained real-world deployment