What Sensors Are Used in Autonomous Robots?

ElecSuppliers Electronics GuideAug 12, 2026

Autonomous robots need sensors to understand their surroundings and make decisions without constant human control. Depending on the robot and its working environment, several types of sensors may be used together.

A mobile robot operating in a warehouse, for example, may need cameras and LiDAR for navigation, while an industrial robot may rely more heavily on position, force and proximity sensors.

Cameras

Cameras are among the most common sensors used in autonomous robots.

A camera provides visual information that can be processed to identify objects, people, road markings, signs and other features.

RGB cameras are useful for general image recognition, while stereo cameras can provide depth information by comparing images from two viewpoints.

Modern robots can also use AI-based computer vision to classify objects and understand their surroundings.

LiDAR

LiDAR measures distance by sending laser pulses and measuring the time required for the reflected light to return.

It can create a detailed representation of the surrounding environment.

LiDAR is widely used in autonomous mobile robots, delivery robots, warehouse robots and other systems that require accurate distance measurements.

Compared with a conventional camera, LiDAR provides direct distance information, which can make it useful for mapping and obstacle detection.

Ultrasonic Sensors

Ultrasonic sensors use sound waves to measure the distance to nearby objects.

They are relatively simple and can be useful for short-range obstacle detection.

Robots may use ultrasonic sensors alongside cameras or LiDAR to detect objects that are very close to the robot.

Their relatively low cost also makes them practical for some consumer and industrial robots.

Radar Sensors

Radar uses radio waves to detect objects and measure distance.

It can work in conditions where cameras may have difficulty, such as darkness, rain or dust.

Radar is therefore useful for robots operating outdoors or in environments with changing lighting conditions.

Some advanced robotic systems combine radar with cameras and other sensors to improve environmental perception.

IMU Sensors

An inertial measurement unit, or IMU, measures motion-related information.

An IMU normally contains accelerometers and gyroscopes and may also include a magnetometer.

It can provide information about acceleration, angular velocity and orientation.

Robots use IMUs to estimate their movement and help maintain a stable estimate of position and orientation.

Encoders

Encoders are commonly installed on robot motors and wheels.

They measure rotational movement and help the controller determine how far a wheel or motor has moved.

Wheel encoders are important for odometry, which estimates the robot's position based on its movement.

However, wheel-based measurements can accumulate errors, especially when wheels slip.

Depth Cameras

Depth cameras provide both visual information and distance information.

Different technologies can be used to obtain depth, including stereo vision, structured light and Time-of-Flight sensing.

Depth cameras are useful for applications such as object detection, robotic manipulation, human detection and indoor navigation.

For compact robots, a 3D camera can combine visual perception and depth sensing in a relatively small module.

Proximity Sensors

Proximity sensors detect nearby objects without necessarily measuring a complete scene.

Depending on the technology, they may use infrared light, electromagnetic fields or other sensing methods.

They are often used for close-range obstacle detection and safety functions.

Force and Torque Sensors

Not all autonomous robots only need to understand their surroundings.

Robotic arms and collaborative robots may also need to understand physical contact.

Force and torque sensors can measure the force applied to the robot or the torque around its joints.

This information can help robots perform tasks such as assembly, gripping, polishing and material handling.

Tactile Sensors

Tactile sensors provide information about physical contact.

They can help robotic systems determine whether an object has been touched, how much pressure is being applied and, in some designs, where contact occurs.

Tactile sensing is particularly useful for robotic hands and manipulation systems.

Temperature Sensors

Temperature sensors are used to monitor both the robot and its operating environment.

They may be installed in motors, batteries, electronic control systems and other components.

Temperature monitoring can help prevent overheating and support predictive maintenance.

GPS and GNSS

Outdoor autonomous robots may use GPS or other GNSS technologies for positioning.

They are useful for applications such as autonomous vehicles, agricultural robots, outdoor delivery robots and inspection systems.

However, satellite positioning can become unreliable indoors or in areas with obstructions, so it is often combined with other positioning technologies.

Why Do Autonomous Robots Use Multiple Sensors?

No single sensor can provide perfect environmental information in every situation.

A camera can recognize objects but may have difficulty determining accurate distance.

LiDAR provides accurate distance information but may not provide the same level of visual information as a camera.

Ultrasonic sensors work well at short distances but provide limited environmental detail.

Combining different sensors can compensate for the weaknesses of individual sensors.

This process is known as sensor fusion.

What Is Sensor Fusion in Robotics?

Sensor fusion combines information from multiple sensors to create a more reliable understanding of the robot's environment.

For example, a robot might combine:

Camera + LiDAR

Camera + IMU

LiDAR + IMU

Radar + camera

Encoder + IMU

The controller or perception system can compare information from different sensors and use it for navigation, mapping and object detection.

How to Choose Sensors for an Autonomous Robot?

Start with the robot's environment and tasks.

Consider whether the robot will operate indoors or outdoors, whether lighting conditions will change, how far it needs to detect objects and how accurately it needs to measure distance.

Cost, size, power consumption and processing requirements should also be considered.

For a compact indoor robot, a depth camera and IMU may provide enough information. A larger outdoor autonomous system may require cameras, LiDAR, radar, GNSS and additional sensors.

3D Cameras in Autonomous Robots

3D cameras are becoming increasingly useful in robotic applications because they provide depth information in addition to conventional images.

Time-of-Flight cameras, for example, can measure distance based on the travel time of light.

They can be used for:

Obstacle detection

Object measurement

Robot navigation

Bin picking

Human detection

3D mapping

Machine vision

The choice of 3D sensing technology depends on the required range, accuracy, frame rate, lighting conditions and application.

Choosing Robot Sensor Suppliers

When sourcing sensors for autonomous robots, consider the sensor's range, accuracy, resolution, frame rate, operating temperature and interface.

For production projects, supplier reliability is also important.

Check whether the supplier can provide technical documentation, evaluation samples, customization and long-term supply.

For applications such as machine vision and robotics, it can also be useful to work with suppliers that understand how the sensor integrates with the robot's software and hardware.

Sensors Are the Foundation of Autonomous Robotics

Autonomous robots rely on sensors to collect information about their surroundings, movement and physical interaction.

Cameras, LiDAR, radar, ultrasonic sensors, IMUs, encoders, depth cameras and force sensors each serve different purposes.

The most suitable combination depends on the robot's environment, navigation requirements, payload, operating range and cost.

As robots become more capable, combining multiple sensors with AI-based perception and sensor fusion will continue to play an important role in autonomous robotic systems.