Autonomy Lab provides end‑to‑end prototype engineering services for autonomous systems, delivering a ROS 2‑based software stack with GPU‑accelerated perception, model‑based control, and custom PCB designs in a single, integrated package. The offering accelerates sensor‑fusion, decision‑making integration, and data‑logging for university labs, research institutes, and industry R&D groups, and includes cloud analytics and open‑source documentation to support rapid validation and reproducibility.
Funding
Funding not disclosed
Founders
Product
Problem
Many research groups and early‑stage product teams lack an integrated, low‑overhead platform for building and testing autonomous systems such as level‑5 ground vehicles, city‑navigation scooters, indoor mapping rigs, and smart‑city testbeds. The absence of a modular stack that combines AI/ML, computer vision, ROS, control theory, and custom electronics forces teams to cobble together disparate components, extending development cycles and increasing risk of hardware‑software mismatches.
Solution
Autonomy Lab delivers end‑to‑end prototype engineering services that turn high‑level autonomy concepts into functional demonstrators ready for validation. By leveraging a unified software stack built on ROS 2, GPU‑accelerated perception pipelines, and model‑based control algorithms, the lab accelerates sensor fusion and decision‑making integration. Custom PCB design and embedded firmware are produced in‑house, ensuring tight coupling between hardware and software while maintaining scalability across vehicle sizes. The resulting platforms include full data‑logging, remote monitoring, and a cloud‑based analytics interface that supports iterative testing and performance benchmarking. All deliverables are packaged with documentation and open‑source code repositories to enable reproducibility in academic or industrial settings. This service model shortens time‑to‑prototype, reduces engineering overhead, and provides a reliable baseline for subsequent productization or research publication.
Target Audience
Primary customers are university robotics labs, research institutes, and industry R&D groups that require rapid prototyping of autonomous vehicles or indoor mapping systems for validation and demonstration purposes. The service also supports engineering curricula that need hands‑on autonomous platform kits for student projects.
Features
- ROS 2‑based middleware with modular nodes for perception, planning, and actuation, supporting both simulation (Gazebo) and real‑world deployment
- GPU‑accelerated computer‑vision stack (YOLO, SLAM, depth estimation) optimized for embedded platforms such as NVIDIA Jetson and Intel Movidius
- Model‑based control suite implementing MPC, LQR, and adaptive controllers, auto‑tuned via reinforcement‑learning pipelines
- In‑house PCB design service delivering compact, high‑current motor drivers, sensor interfaces, and CAN/FlexRay communication boards
- Integrated data‑logging framework with time‑synchronized ROS bags and cloud upload via secure MQTT for post‑run analysis
- Automated simulation‑to‑hardware transfer tools that generate configuration files and firmware binaries from a single parameter set
- Open‑source GitHub repository with CI/CD pipelines, unit tests, and documentation to facilitate knowledge transfer and reproducibility
- Compliance testing package covering safety standards (ISO 26262, IEC 61508) for research‑grade autonomous platforms