Difference between revisions of "Unmanned Ground Vehicles"
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== Autonomous UGVs == | == Autonomous UGVs == | ||
− | UGVs can occupy a broad spectrum of | + | UGVs can occupy a broad spectrum of autonomous capability. |
=== Open Loop/Sensorless Robots === | === Open Loop/Sensorless Robots === | ||
The most basic autonomy possible. The robot blindly repeats a set of pre-programmed motions | The most basic autonomy possible. The robot blindly repeats a set of pre-programmed motions | ||
− | without any | + | without any sensor feedback. |
− | Without | + | Without sensors, the UGV doesn’t know where it is and can’t detect obstacles around itself. UGVs using this approach aren’t very |
useful so open loop autonomy is not common for this class of robots. Industrial robot arms can be effective with open loop operation in applications where they just need to perform some repetitive motion over and over. However, this still requires lots of calibration/tuning and the environment must be maintained in the state that the robot is expecting. | useful so open loop autonomy is not common for this class of robots. Industrial robot arms can be effective with open loop operation in applications where they just need to perform some repetitive motion over and over. However, this still requires lots of calibration/tuning and the environment must be maintained in the state that the robot is expecting. | ||
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=== Line Following === | === Line Following === | ||
− | [[Line Following]] is a method of | + | [[Line Following]] is a method of autonomous movement in which the UGV follows a line on the ground. Common approaches for detecting the line include optical sensors which detect the color of the line or magnetic sensors ([##ITEM2295## MGS1600]) which detect magnetic tape. The line layout can simply go from point A to B or scale up to a complex network of forks and waypoints. When manually driven, the robot may move freely without the line. This method is far easier and cheaper to develop than allowing the robot to freely roam in the space. The trade-offs are that the line/tape must be placed beforehand (and maintained) and the robot’s autonomous movement is restricted to the lines. |
− | The robot in the video below is a line follower that uses the [ | + | The robot in the video below is a line follower that uses the [##ITEM2295## RoboteQ MGS1600GY Magnetic Guide Sensor] to follow magnetic tape on the ground. The robot demonstrates stopping at waypoints and selecting routes at forks. |
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=== Robots that don't use Mapping/SLAM === | === Robots that don't use Mapping/SLAM === | ||
− | The UGV can move freely but doesn’t maintain an | + | The UGV can move freely but doesn’t maintain an obstacle map of its environment. The UGV may implement an obstacle detection system and can use this information to prevent collisions. The lack of a map allows the use of less powerful computers and sensors but prevents the robot from being able to reliably navigate around obstacles or generate paths that avoid previously encountered obstacles. Navigation decisions are made with only the current information visible to the robot's sensors. |
− | If the UGV has a | + | If the UGV has a positioning system, it can travel to waypoints. The video below shows our [##ITEM2880## Mini-IPS Robot] in action. The robot |
− | uses the | + | uses the Marvelmind Indoor Positioning System and wheel encoders to position itself. The robot runs on ROS and the video shows it traveling between user-defined waypoints. The [##ITEM2880## Mini-IPS Robot] is also equipped with a 2D Lidar that it uses for obstacle_detection. |
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The UGV moves freely while generating and maintaining a map of obstacles encountered in its | The UGV moves freely while generating and maintaining a map of obstacles encountered in its | ||
− | environment, usually with the | + | environment, usually with the SLAM algorithm. Use of |
− | + | mapping automatically equips the robot with powerful positioning and obstacle detection systems. The positioning system enables real-time tracking of the robot's location and waypoint travel. The navigation system can use the map to plan a path to a waypoint that avoids any previously encountered obstacles. These features greatly enhance the capabilities of the robot. | |
− | waypoint travel. The | ||
− | plan a path to a waypoint that avoids any previously encountered obstacles. These features greatly enhance the capabilities of the robot. | ||
− | The [ | + | The [##ITEM2420## Autonomous Agricultural Robot] in the video below uses 2D Lidars for 2D SLAM when |
− | indoors and a Zed | + | indoors and a Zed depth camera for 3D SLAM when outdoors. The positioning system also fuses measurements from encoders, an IMU, and RTK GPS. The robot can travel to user-defined waypoints while avoiding both expected and unexpected obstacles along the way. |
{{#evt: | {{#evt: |
Revision as of 20:16, 14 September 2020
Unmanned Ground Vehicles (UGVS) are ground-based robots that operate without any humans onboard. They can be remote-controlled or autonomous.
Contents
Remote-Controlled UGVs
Autonomous UGVs
UGVs can occupy a broad spectrum of autonomous capability.
Open Loop/Sensorless Robots
The most basic autonomy possible. The robot blindly repeats a set of pre-programmed motions without any sensor feedback. Without sensors, the UGV doesn’t know where it is and can’t detect obstacles around itself. UGVs using this approach aren’t very useful so open loop autonomy is not common for this class of robots. Industrial robot arms can be effective with open loop operation in applications where they just need to perform some repetitive motion over and over. However, this still requires lots of calibration/tuning and the environment must be maintained in the state that the robot is expecting.
When we sell programmable robots without a remote control method, we often use an open loop approach and program them to cycle through a set of preset movements, e.g. drive forward, drive backwards, turn left, turn right. The robots in the following video are examples of this.
Line Following
Line Following is a method of autonomous movement in which the UGV follows a line on the ground. Common approaches for detecting the line include optical sensors which detect the color of the line or magnetic sensors ([##ITEM2295## MGS1600]) which detect magnetic tape. The line layout can simply go from point A to B or scale up to a complex network of forks and waypoints. When manually driven, the robot may move freely without the line. This method is far easier and cheaper to develop than allowing the robot to freely roam in the space. The trade-offs are that the line/tape must be placed beforehand (and maintained) and the robot’s autonomous movement is restricted to the lines.
The robot in the video below is a line follower that uses the [##ITEM2295## RoboteQ MGS1600GY Magnetic Guide Sensor] to follow magnetic tape on the ground. The robot demonstrates stopping at waypoints and selecting routes at forks.
Robots that don't use Mapping/SLAM
The UGV can move freely but doesn’t maintain an obstacle map of its environment. The UGV may implement an obstacle detection system and can use this information to prevent collisions. The lack of a map allows the use of less powerful computers and sensors but prevents the robot from being able to reliably navigate around obstacles or generate paths that avoid previously encountered obstacles. Navigation decisions are made with only the current information visible to the robot's sensors.
If the UGV has a positioning system, it can travel to waypoints. The video below shows our [##ITEM2880## Mini-IPS Robot] in action. The robot uses the Marvelmind Indoor Positioning System and wheel encoders to position itself. The robot runs on ROS and the video shows it traveling between user-defined waypoints. The [##ITEM2880## Mini-IPS Robot] is also equipped with a 2D Lidar that it uses for obstacle_detection.
Robots that use Mapping/SLAM
The UGV moves freely while generating and maintaining a map of obstacles encountered in its environment, usually with the SLAM algorithm. Use of mapping automatically equips the robot with powerful positioning and obstacle detection systems. The positioning system enables real-time tracking of the robot's location and waypoint travel. The navigation system can use the map to plan a path to a waypoint that avoids any previously encountered obstacles. These features greatly enhance the capabilities of the robot.
The [##ITEM2420## Autonomous Agricultural Robot] in the video below uses 2D Lidars for 2D SLAM when indoors and a Zed depth camera for 3D SLAM when outdoors. The positioning system also fuses measurements from encoders, an IMU, and RTK GPS. The robot can travel to user-defined waypoints while avoiding both expected and unexpected obstacles along the way.