Simulabs builds robot systems through software‑hardware co‑design, adjusting hardware such as gripper geometry and sensor placement to simplify control problems. Their modular architecture supports pilot deployments with industrial partners, featuring fallback mechanisms that enable easy deployment and continuous improvement from real‑world operation.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers face high costs and complexity when integrating robotic automation because traditional robots are designed for fixed tasks and require extensive tuning of control systems, making deployment time‑consuming and limiting flexibility for varied production needs.
Solution
Simulabs creates industrial robots through a software‑hardware co‑design methodology that tailors mechanical elements—such as gripper shape, compliance, and sensor placement—to simplify the underlying control problems. By adjusting hardware to match the control software, the robots achieve more reliable operation with less computational overhead. Their modular architecture enables rapid reconfiguration and scaling across different workcells, while built‑in fallback mechanisms allow the robots to continue operating safely during learning phases. Pilot deployments with industrial partners demonstrate that the robots can improve performance autonomously as they gather real‑world data, reducing the need for extensive offline programming and accelerating time‑to‑value for manufacturers seeking adaptable automation.
Target Audience
Primary customers are mid‑size to large manufacturers in sectors such as automotive, consumer goods, and electronics that require flexible, quickly deployable robotic solutions for assembly, material handling, and custom part processing.
Features
- Co‑design process that iteratively aligns mechanical design with control algorithms to reduce control complexity
- Adjustable gripper geometry and compliance mechanisms that can be reconfigured for diverse part handling tasks
- Integrated sensor placement strategy providing high‑fidelity feedback for robust closed‑loop control
- Modular hardware and software stack allowing plug‑and‑play upgrades and easy reconfiguration of robot capabilities
- Fallback safety and learning mechanisms that let robots operate safely while continuously refining performance from real‑world pilot data
- Compatibility with existing industrial equipment and standards to facilitate seamless integration into current production lines