Difference between revisions of "Lidar"
(→Overview) |
|||
| Line 5: | Line 5: | ||
=== Overview === | === Overview === | ||
| − | 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. | + | '''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. | + | '''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. |
| − | Sensor Pros: | + | '''Sensor Pros:''' |
*Data is easily processed, allowing the use of cheaper microcontrollers | *Data is easily processed, allowing the use of cheaper microcontrollers | ||
*Less expensive than 2D Lidar | *Less expensive than 2D Lidar | ||
*Good detection range, update rate, and accuracy | *Good detection range, update rate, and accuracy | ||
*Can be used for 1D positioning or following applications | *Can be used for 1D positioning or following applications | ||
| − | Sensor Cons: | + | |
| + | '''Sensor Cons:''' | ||
*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. | *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. | *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. | ||
| Line 25: | Line 26: | ||
=== Overview === | === Overview === | ||
| − | 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. | + | '''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. | + | '''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. |
| − | Sensor Pros: | + | '''Sensor Pros:''' |
*Less data to process than a 3D Lidar | *Less data to process than a 3D Lidar | ||
*Much more coverage than 1D sensors like IR and 1D Lidar | *Much more coverage than 1D sensors like IR and 1D Lidar | ||
*Can be used to generate a 2D map and utilize 2D SLAM | *Can be used to generate a 2D map and utilize 2D SLAM | ||
*Good detection range and update rate | *Good detection range and update rate | ||
| − | Sensor Cons: | + | |
| + | '''Sensor Cons:''' | ||
*Can only see obstacles on a single horizontal plane, unable to see above and below the sensor | *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 | *More data than 1D sensors, usually requiring a small computer to use | ||
| Line 60: | Line 62: | ||
=== Overview === | === Overview === | ||
| − | 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. | + | '''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. | + | '''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. |
| − | Sensor Pros: | + | '''Sensor Pros:''' |
*Full coverage of the robot’s environment | *Full coverage of the robot’s environment | ||
*Can be used to generate a 3D map and utilize 3D SLAM | *Can be used to generate a 3D map and utilize 3D SLAM | ||
| Line 70: | Line 72: | ||
*Works in 3D environments where the robot is pitching, rolling, and changing in elevation. Can generate 3D position and orientation estimates. | *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. | *Can detect obstacles above and below itself, which a 2D lidar would miss. | ||
| − | Sensor Cons: | + | |
| + | '''Sensor Cons:''' | ||
*Expensive | *Expensive | ||
*Generates a large amount of data, which requires a more powerful computer to process and make use of | *Generates a large amount of data, which requires a more powerful computer to process and make use of | ||
Revision as of 14:41, 1 September 2020
LIDAR (short for Light Detection And Ranging), uses near infrared light to image 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.
Contents
1D Lidar
Overview
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.
Sensor Pros:
- 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
Sensor Cons:
- 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.
Products
LIDAR-Lite v3 Laser Rangefinder
2D Lidar
Overview
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.
Sensor Pros:
- 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
Sensor Cons:
- 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
SLAM Application
Products
YDLIDAR X4
YDLIDAR G4
Hokuyo URG-04LX-UG01
Hokuyo UST-10LX
Hokuyo UST-20LX
Hokuyo UTM-30LX
3D Lidar
Overview
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.
Sensor Pros:
- 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.
Sensor Cons:
- Expensive
- 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
Example Application
Footage of the SPAR autonomous security robot. 3D SLAM footage starts at 0:24.