testbeds-for-mobility-tasks

Service Description

This service provides AI-Users with access to a diverse fleet of autonomous mobile robots (AMRs) and quadrupeds, including platforms like the Booster humanoid, Spot, Mini-Cheetah, Avular wheeled robots, and custom-built systems (e.g. TURTLE soccer robots). Designed for experimentation in real-world manufacturing environments, this service enables you to test and refine intralogistics solutions, such as moving products from point A to B across a manufacturing hall.

For AI-Users in manufacturing, logistics, and automation, this testbed is ideal for exploring AI-powered robot control, localization, task planning, and multi-agent systems. Whether you’re developing algorithms for flexible production, self-adaptive manufacturing, or human-robot interaction, this service provides the hardware and environment to validate your solutions in a dynamic, industrial setting.

Customer Benefits:

  • Quantitative: Reduce intralogistics errors through AI-driven mobility optimization.
  • Qualitative: Accelerate the development of autonomous systems with real-world testing on state-of-the-art robotic platforms.

What You Provide:

  • Your AI models, algorithms, or control systems for mobility tasks.
  • Specific use cases or scenarios you want to test (e.g., obstacle avoidance, multi-robot coordination).
  • Any custom data or software requirements for integration.

What We Provide:

  • Access to a variety of mobile robots (humanoid, quadruped, wheeled) and an experiment environment.
  • Technical support for setup, experimentation, and data collection.
  • A detailed report with performance metrics, insights, and recommendations for further optimization.
Expected results:

A comprehensive report including:

  • Performance metrics for mobility tasks.
  • Insights into AI model behavior and optimization opportunities.
  • Recommendations for improving intralogistics efficiency.
Methodology:
  1. Setup: Configuration of robots and environment for your use case.
  2. Experimentation: Testing of AI models, algorithms, or control systems.
  3. Data Collection: Performance metrics and behavioral data.
  4. Analysis: Evaluation of results and insights.
  5. Reporting: Delivery of a detailed report with recommendations.
Target:

Manufacturing, Logistics, Automation, Robotics, AI Development, Warehousing, Industrial Automation.

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