LIDAR (short for Light Detection And Ranging), uses near infrared light to measure distances to objects. The narrow laser-beam that’s emitted is capable of mapping physical features at high resolutions. Offering precise positioning while targeting a wide range of materials, LIDAR is a very powerful feedback system that can be used in many robotic applications.
Obstacle Detection: Detects obstacles in a straight, narrow beam of light. Lidar will be more accurate (and expensive) than simple IR sensors. Lidars that detect out to 60+ feet are common.
Ideal operating conditions: Lidar can become erratic when exposed to sunlight interference. Some sensors will work perfectly outside while others may be fine with ambient sunlight and have problems only when pointed towards the sun. The rest range from slightly noisy to completely unusable outside.
- Data is easily processed, allowing the use of cheaper microcontrollers
- Less expensive than 2D Lidar
- Good detection range, update rate, and accuracy
- Can be used for 1D positioning or following applications
- Only detects obstacles in a narrow beam. If these are the primary obstacle detection sensors on a robot then several of them are required and there will still be big gaps in the detection zone – between the beams and above/below them.
- You may be tempted to sweep the sensor using an RC servo or something, but this generally doesn’t work very well. You’re better off buying a cheap 2D lidar at that point.
- Can be vulnerable to dirt/dust and scratches.
Obstacle Detection: Detects obstacles surrounding the robot. The 2D lidar generates a planar ring of points that extend to the closest obstacle in all directions. Able to create a rough map of the robot’s immediate surroundings.
Ideal operating conditions: Installed at a height where obstacles are expected to be encountered. Some Lidars are sensitive to sunlight, depending on the specific model and design.
- Less data to process than a 3D Lidar
- Much more coverage than 1D sensors like IR and 1D Lidar
- Can be used to generate a 2D map and utilize 2D SLAM
- Good detection range and update rate
- Can only see obstacles on a single horizontal plane, unable to see above and below the sensor
- More data than 1D sensors, usually requiring a small computer to use
- Unreliable when the robot pitches and rolls, due to the detection plane intersecting the ground
Obstacle Detection: Detects obstacles surrounding the robot in 3D space. The 3D lidar generates a cloud of points that extend out from the sensor in all directions horizontally and 30 degrees above and below the sensor vertically. Able to create a detailed map of the robot’s surroundings, including obstacles above the robot and below the lidar.
Ideal operating conditions: Installed on the top of the robot, low enough to the ground where the 30 degree window is able to see the area directly in front of the robot. Some lidars are sensitive to sunlight, depending on the specific model and design.
- Full coverage of the robot’s environment
- Can be used to generate a 3D map and utilize 3D SLAM
- Reliable due to the large number of data points to base position off of
- Works in 3D environments where the robot is pitching, rolling, and changing in elevation. Can generate 3D position and orientation estimates.
- Can detect obstacles above and below itself, which a 2D lidar would miss.
- Generates a large amount of data, which requires a more powerful computer to process and make use of
- Limited viewing angle, restricts where the sensor can be placed effectively
Footage of the SPAR autonomous security robot. 3D SLAM footage starts at 0:24.