Sensor Fusion

Sensor fusion combines data from multiple sources to create a reliable model of reality. This guide details how it works, its necessity in hardware, and implementation strategies for startups.

This article defines the gyroscope within a startup context, explaining angular velocity, comparing it to accelerometers, and detailing the challenges of integration and sensor drift.

An essential breakdown of magnetometers for entrepreneurs, explaining how these sensors define orientation, integrate with other hardware, and solve navigation challenges in modern technology.

LIDAR uses laser pulses to generate precise 3D maps. This guide explains the mechanics, compares it to other sensors, and outlines strategic considerations for hardware and software founders.

Robotic perception turns raw sensor data into actionable understanding. This guide defines the term, explores the technical stack, and analyzes the strategic challenges for hardware startups.

An IMU combines sensors to track force, angular rate, and magnetic fields. This guide explains their mechanics, use cases, and how to select the right one for your hardware startup.

An exploration of odometry in startup contexts, covering how sensors track relative position, the inevitability of accumulation errors, and why it matters for robotics and hardware automation.

An introduction to SLAM for founders, explaining how robots map and navigate simultaneously, comparing sensor technologies, and outlining the strategic business decisions behind autonomous systems.

The Kalman Filter is an algorithm that estimates true values from noisy data. This article explains its mechanics, comparisons to other methods, and utility for startup founders.

RADAR is a detection system using radio waves to track objects. This article explores its mechanics, compares it to LiDAR, and analyzes its critical role in modern hardware startups.