Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

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

Christopher Bohn, Florian Siebenrock, Janne Bosch, Tobias Hetzner, Samuel Mauch, Philipp Reis, Timo Staudt, Manuel Hess, Ben-Micha Piscol, Sören Hohmann

TL;DR

This paper introduces ZeloS, a modular research platform designed for early-stage validation of automated driving methods. It details a hardware design with five modules supporting all-wheel steering and drive, integrated with a centralized automation architecture and a safety watchdog to enable safe, flexible experimentation. The authors present a model-based planning and tracking pipeline, including a convex, model-predictive motion planner and a two-stage tracking controller, complemented by a Gazebo-based digital twin for fast software-in-the-loop testing. Experimental results demonstrate reliable navigation, obstacle avoidance, and low tracking error, highlighting ZeloS as a practical, low-cost platform for validating automated driving methods early in development and supporting ISO26262-aligned safety considerations.

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.

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

TL;DR

This paper introduces ZeloS, a modular research platform designed for early-stage validation of automated driving methods. It details a hardware design with five modules supporting all-wheel steering and drive, integrated with a centralized automation architecture and a safety watchdog to enable safe, flexible experimentation. The authors present a model-based planning and tracking pipeline, including a convex, model-predictive motion planner and a two-stage tracking controller, complemented by a Gazebo-based digital twin for fast software-in-the-loop testing. Experimental results demonstrate reliable navigation, obstacle avoidance, and low tracking error, highlighting ZeloS as a practical, low-cost platform for validating automated driving methods early in development and supporting ISO26262-aligned safety considerations.

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.
Paper Structure (32 sections, 33 equations, 12 figures)

This paper contains 32 sections, 33 equations, 12 figures.

Table of Contents

  1. Introduction
  2. Review on Existing Concepts
  3. Setup of the Research Platform
  4. Overview
  5. Vehicle Body Design
  6. Driving and Steering Actuators
  7. Hardware Interface
  8. Computational Units
  9. Automation Architecture
  10. Safety Concept
  11. Modeling of the Research Platform
  12. Tire Model
  13. Tire Chassis Coupling
  14. Horizontal Dynamics
  15. Sensor Setup and Localization
  16. ...and 17 more sections

Figures (12)

  • Figure 1: ZeloS, a versatile research platform.
  • Figure 2: The CAD drawing of the vehicle body reveals the modular design.
  • Figure 3: Hardware Architecture of ZeloS.
  • Figure 4: Functional Architecture of ZeloS.
  • Figure 5: Coordinate frames used for the localization. Solid gray line: continuous transformation, dotted gray lines: discontinuous transformations.
  • ...and 7 more figures