See What Lidar Robot Navigation Tricks The Celebs Are Utilizing
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lidar explained robot navigation (great site)
LiDAR robot navigation is a complicated combination of mapping, localization and path planning. This article will introduce these concepts and explain how they work together using a simple example of the robot achieving its goal in a row of crop.
LiDAR sensors are relatively low power requirements, which allows them to prolong the battery life of a robot and decrease the need for raw data for localization algorithms. This allows for a greater number of versions of the SLAM algorithm without overheating the GPU.
LiDAR Sensors
The central component of lidar systems is its sensor which emits laser light in the environment. These light pulses strike objects and bounce back to the sensor at various angles, depending on the structure of the object. The sensor records the amount of time it takes for each return and then uses it to calculate distances. Sensors are placed on rotating platforms, which allow them to scan the surrounding area quickly and at high speeds (10000 samples per second).
LiDAR sensors are classified based on their intended airborne or terrestrial application. Airborne lidars are often connected to helicopters or an UAVs, which are unmanned. (UAV). Terrestrial LiDAR is usually installed on a robotic platform that is stationary.
To accurately measure distances, the sensor needs to know the exact position of the robot at all times. This information is gathered using a combination of inertial measurement unit (IMU), GPS and time-keeping electronic. These sensors are used by lidar vacuum systems to calculate the precise position of the sensor within the space and time. The information gathered is used to create a 3D representation of the environment.
LiDAR scanners can also identify different types of surfaces, which is particularly useful when mapping environments that have dense vegetation. For instance, if an incoming pulse is reflected through a forest canopy it is likely to register multiple returns. Typically, the first return is attributable to the top of the trees and the last one is attributed to the ground surface. If the sensor records these pulses in a separate way this is known as discrete-return vacuum lidar.
The Discrete Return scans can be used to study surface structure. For instance, a forested region could produce a sequence of 1st, 2nd and 3rd return, with a final large pulse representing the ground. The ability to separate and record these returns in a point-cloud allows for precise terrain models.
Once a 3D model of the environment is built and the robot is capable of using this information to navigate. This involves localization and creating a path to take it to a specific navigation "goal." It also involves dynamic obstacle detection. This is the process of identifying new obstacles that aren't present in the map originally, and then updating the plan in line with the new obstacles.
LiDAR robot navigation is a complicated combination of mapping, localization and path planning. This article will introduce these concepts and explain how they work together using a simple example of the robot achieving its goal in a row of crop.
LiDAR sensors are relatively low power requirements, which allows them to prolong the battery life of a robot and decrease the need for raw data for localization algorithms. This allows for a greater number of versions of the SLAM algorithm without overheating the GPU.
LiDAR Sensors
The central component of lidar systems is its sensor which emits laser light in the environment. These light pulses strike objects and bounce back to the sensor at various angles, depending on the structure of the object. The sensor records the amount of time it takes for each return and then uses it to calculate distances. Sensors are placed on rotating platforms, which allow them to scan the surrounding area quickly and at high speeds (10000 samples per second).
LiDAR sensors are classified based on their intended airborne or terrestrial application. Airborne lidars are often connected to helicopters or an UAVs, which are unmanned. (UAV). Terrestrial LiDAR is usually installed on a robotic platform that is stationary.
To accurately measure distances, the sensor needs to know the exact position of the robot at all times. This information is gathered using a combination of inertial measurement unit (IMU), GPS and time-keeping electronic. These sensors are used by lidar vacuum systems to calculate the precise position of the sensor within the space and time. The information gathered is used to create a 3D representation of the environment.
LiDAR scanners can also identify different types of surfaces, which is particularly useful when mapping environments that have dense vegetation. For instance, if an incoming pulse is reflected through a forest canopy it is likely to register multiple returns. Typically, the first return is attributable to the top of the trees and the last one is attributed to the ground surface. If the sensor records these pulses in a separate way this is known as discrete-return vacuum lidar.
The Discrete Return scans can be used to study surface structure. For instance, a forested region could produce a sequence of 1st, 2nd and 3rd return, with a final large pulse representing the ground. The ability to separate and record these returns in a point-cloud allows for precise terrain models.
Once a 3D model of the environment is built and the robot is capable of using this information to navigate. This involves localization and creating a path to take it to a specific navigation "goal." It also involves dynamic obstacle detection. This is the process of identifying new obstacles that aren't present in the map originally, and then updating the plan in line with the new obstacles.
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