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Скачать или смотреть kiwibot-V4_Benawake-TFMini-Plus12m-LIDAR(Sensors_Testing)(TestTrack#1)

  • BetaCode
  • 2020-09-05
  • 172
kiwibot-V4_Benawake-TFMini-Plus12m-LIDAR(Sensors_Testing)(TestTrack#1)
ROS2ROSKiwibotNavigationPoint ClouldObstacle AvoidanceRobotRoboticsEdge DetectorCliff SensorDistance SensorBenawakeIRInfrared
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Описание к видео kiwibot-V4_Benawake-TFMini-Plus12m-LIDAR(Sensors_Testing)(TestTrack#1)

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Programmer/Github: https://github.com/JohnBetaCode

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Variables to Test:
We tested the Benawake TFMini-Plus12m LIDAR as cliff sensors in the configuration for our new robot, the Kiwibot 4.0. The robot was driven in different velocities to verify its reaction when faces an aggressive frontal cliff. This was an extreme test scenario as we will face curbs that are not too high; however, it is a good scenario to demonstrate the application reliability.


These tests consisted of moving the robot on the edge of the platform. to check if it falls sideways. The robot was driven alongside an edge. This is a real-world scenario as we know that many of the Kiwibot rollovers occur when driving at the very edge.


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Test:
The main objective of this test was to check if the prototype of the piece where will be located the sensors, works, and had a correct performance.

This test consisted of drive all the test track and try to put the robot in a risk scenery, like in the edge of the sidewalk, or try to make him fall head-on on a sidewalk.

The velocity used during the lap in the test track was 60.
It's important to highlight that this test track has a high level of difficulty, the sidewalks are very small, very few people manage to complete it without falls.
The video have two videos, the console and the robot in the track, to check the functionality, you can see that when the robot stop, the console show a message that said " El robot se ha detenido por CliffSensors" or " El robot se ha detenido por Lidar".



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Testing comments:
Please read carefully the following comments as they are potential issues that we would face in the real world; however, we were able to develop a reliable application that would work in most of the cases.

1. When the robot is facing sharp turns, sometimes it will not be able to see the inner corner; nevertheless, the robot will not fall down, we classified it as a low-risk scenario, but it is always good to show this kind of issues. Please watch the first 10 seconds.


2. Having the right setup on the IMU is critical to guarantee the desired behavior of the robot when it is uphill or downhill (In a ramp which is a common scenario). We faced this issue and we try to tune it as much as we can in order to make it works.

This is a brief explanation of how the sensors deactivation works when the robot is on a ramp. Firstly it will sense a difference between surfaces in two different times (Say 100 ms), this will allow us to identify an inclination or declination on the surface. This is a good approach, but in the practice, the sensors have different behavior, for that reason, we decided to use the IMU in combination with some timers to deactivate the action of all sensors when it is moving on a ramp. We basically extract the current pitch angle (Supposing it is 0 when we are on a flat surface) and deactivate the action of the sensor based on some conditions. So when the IMU has already an offset when it is on a flat surface (Say the pitch now is 9 instead of 0) it will be so though to tune each robot with the explained offset.



This feature is important as we want to help the supervisor with a smart deactivation instead of pressing a key every single time it faces this scenario.

3. During testing, we gathered some ideas on how to improve the application, but so far we believe this is a reliable application that can be used in the real world, it will not allow the robot to fall down from the sidewalk.


4. It's important to have clear that the manufacturing team gave us the piece assembly in the robot with the sensors, do the issues during the assembly we don't have knowledge.

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Tester/Programmer:
Camilo Alvis:

  / camiloalvis  
https://github.com/kmilo7204

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