LiDAR vs Radar: Why Mobile Robots Prefer Laser Sensors

Radar and LiDAR in Modern Sensing Systems

In recent years, both radar and LiDAR (Light Detection and Ranging) technologies have seen rapid growth across multiple industries. From autonomous driving and robotics to smart transportation and security systems, these sensing technologies play a critical role in environmental perception.

In the context of mobile robots, however, LiDAR has gradually become the dominant sensing solution—especially for indoor navigation and localization. To understand why, it is important to examine the fundamental differences between traditional radar and LiDAR.

What Is LiDAR?

LiDAR is not a new technology, but it gained widespread attention with the rise of service robots and autonomous vehicles. Today, LiDAR is also widely used in AR/VR, smart cities, ocean exploration, 3D mapping, and industrial automation.

At its core, LiDAR is a sensor capable of capturing high-precision 2D or 3D spatial information. Much like human vision, it allows machines to perceive their surroundings with fine geometric detail.

A typical LiDAR system consists of three main components:

A laser transmitter
A receiver
A signal processing unit

LiDAR works by emitting laser pulses toward a target and measuring the reflected signals. By comparing the transmitted and returned signals, the system can calculate key parameters such as distance, angle, shape, and relative position of surrounding objects.

This ability makes LiDAR particularly suitable for mapping, localization, obstacle detection, and tracking—all of which are fundamental to autonomous robot navigation.

What Is Traditional Radar?

Radar technology dates back to World War II, where it was primarily used for detecting aircraft and monitoring airspace. Traditional radar systems operate by transmitting radio waves and analyzing their reflections from objects.

Using electromagnetic waves, radar can determine the distance and relative velocity of targets, and it remains highly effective in applications such as aviation, maritime navigation, and long-range surveillance.

However, radar systems typically offer lower spatial resolution compared to LiDAR, which limits their usefulness in fine-grained indoor perception tasks.

Key Differences Between Radar and LiDAR

Although both radar and LiDAR are based on active sensing, their physical characteristics lead to significant performance differences—especially in robotics applications.

Resolution and Accuracy

Radar relies on radio waves with relatively long wavelengths, which results in coarser spatial resolution. This makes it difficult to accurately detect small obstacles or detailed environmental features.

LiDAR, on the other hand, uses laser beams with much shorter wavelengths, enabling high-resolution distance measurements and precise environmental mapping. This level of accuracy is critical for indoor mobile robots operating in confined spaces.

Interference and Signal Robustness

Radar signals are more susceptible to electromagnetic interference from other devices and environmental factors. Additionally, radio waves can be easier to detect or intercept in certain applications.

LiDAR signals travel in narrow, straight beams, making them highly directional and difficult to intercept. Since there are relatively few natural sources of laser interference in indoor environments, LiDAR systems also demonstrate strong resistance to external noise.

Suitability for Mobile Robots

For indoor mobile robots, perception systems must meet strict requirements:

High localization accuracy
Reliable obstacle detection
Compact size and low power consumption

LiDAR meets these requirements particularly well. Compared to traditional radar, LiDAR sensors are generally smaller, lighter, and better suited for integration into mobile robot platforms.

This is one of the key reasons why 2D LiDAR has become the standard sensor for indoor SLAM, navigation, and obstacle avoidance systems.

Why LiDAR Is Preferred in Autonomous Navigation

In practical robot deployments, LiDAR plays a central role in:

SLAM (Simultaneous Localization and Mapping)
Real-time obstacle detection
Path planning and motion control

While radar excels at long-range detection and harsh outdoor conditions, LiDAR offers the precision and environmental detail required for indoor autonomous navigation.

As a result, most service robots—such as delivery robots, cleaning robots, and inspection robots—rely on LiDAR as their primary perception sensor.

Conclusion

Both radar and LiDAR are powerful sensing technologies, but they serve different purposes. For mobile robots operating indoors, LiDAR provides clear advantages in terms of accuracy, resolution, interference resistance, and system integration.

These strengths make LiDAR the preferred choice for building reliable autonomous navigation and localization systems in modern service robots.

Keywords: Lidar,Industry Knowledge

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LiDAR vs Radar: Why Mobile Robots Prefer Laser Sensors

Radar and LiDAR in Modern Sensing Systems

What Is LiDAR?

What Is Traditional Radar?

Key Differences Between Radar and LiDAR

Resolution and Accuracy

Interference and Signal Robustness

Suitability for Mobile Robots

Why LiDAR Is Preferred in Autonomous Navigation

Conclusion

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