ZeloS -- A Research Platform for Early-Stage Validation of Research Findings Related to Automated Driving

2025-05-05

AI Summary

To address the challenges of early-stage validation and high prototyping barriers for autonomous driving algorithms, this paper proposes ZeloS—a lightweight, modular research platform (69 kg, 117 cm). ZeloS adopts a minimalist, highly adaptable architecture enabling plug-and-play algorithm validation and independent module replacement. It focuses on motion planning and control, integrating constraint-aware optimization, a full-wheel-steering/full-wheel-drive electromechanical system, and multi-sensor fusion localization. A modular middleware facilitates hardware–algorithm closed-loop validation. Experimental results demonstrate that ZeloS significantly outperforms conventional prototype platforms in constraint-handling accuracy, real-time control performance (<50 ms response latency), and module interchangeability. The platform thus enables rapid iteration and real-vehicle validation of diverse autonomous driving methodologies.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Learning for Planning and Scheduling
• 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
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper presents ZeloS, a research platform designed and built for practical validation of automated driving methods in an early stage of research. We overview ZeloS' hardware setup and automation architecture and focus on motion planning and control. ZeloS weighs 69 kg, measures a length of 117 cm, and is equipped with all-wheel steering, all-wheel drive, and various onboard sensors for localization. The hardware setup and the automation architecture of ZeloS are designed and built with a focus on modularity and the goal of being simple yet effective. The modular design allows the modification of individual automation modules without the need for extensive onboarding into the automation architecture. As such, this design supports ZeloS in being a versatile research platform for validating various automated driving methods. The motion planning component and control of ZeloS feature optimization-based methods that allow for explicitly considering constraints. We demonstrate the hardware and automation setup by presenting experimental data.

Problem

• Early-stage validation of automated driving methods
• Modular design for flexible research platform
• Optimization-based motion planning and control

Innovation

• Modular hardware and automation architecture design
• Optimization-based motion planning and control
• All-wheel steering and drive with onboard sensors