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TASK 4. AMAZON WAREHOUSE: OMPL

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INTRODUCTION The objective of this task is to implement the logic that allows an holonomic logistics robot to deliver shelves to deliver shelves to the required place by making use of the location of the robot. The robot is equipped with a map and knows its current location in it. The main objective is to find a path using OMPL(Open Motion Planning Library). To achieve this, it has been necessary to create a state machine composed of the following states: With the states of lift and put down being built-in functions. In this post I am going to cover the following points:  Dimensions OMPL OMPL: Obstacles. OMPL: Dimensions. OMPL: Plan Navigation Videos  Conclusion DIMENSIONS In order to work in the same units and provide coherence and ease to calculations, it is necessary to relate the dimensions of the map to those of the 3D world. Map dimensions: Height: 415 pixels Width: 279 pixels Real-world dimensions: Long: 20.62 m Wide: 13.6 m  However, both do not have the origi...
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TASK 3. AUTOPARKING

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 INTRODUCTION   The objective of this practice is to implement the logic that allows an Ackermann car to park in line autonomously.  In this post I am going to include just solutions with Ackermann car using RADI ROS2 since the difference with the Holonomic car are its movement dynamics; which are easier to work with using Holonomic car. Along this explanation, I am going to cover the following topics: Parse laser  State 1: Align State 2: Find space  State 3: Move ahead State 4: Turn  State 5: Go back State 6 and 7: Park maneuvers   PARSE LASER Throughout the entire exercise, it will be necessary to handle the three lasers in different stages to successfully execute the task assigned to them. Therefore, I have deemed it necessary that within the laser values, if they fall within the minimum and maximum range, they should be stored in a secondary array that includes, at a position, (dist, angle), where "dist" represents the laser distance , and "angle...
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TASK 2: RESCUE PEOPLE

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    INTRODUCTION The objective of this practice is to implement the logic that allows a quad-rotor to recognize the faces of lost people and save their locations in order to perform a subsequent rescue maneuver. Besides, the quad-rotor batteries are limited and each 10 minutes, the quad-rotor should come back to charge again. Along this explanation, I am going to cover the following topics: Coordinates conversion: from GPS to UTM State Machine -> Phase 1: Take off State Machine -> Phase 2: Go to survivors State Machine -> Phase 3: Finding people State Machine -> Phase 4: Go to boat State Machine -> Phase 5: Recharging State Machine -> Phase 6: Landing Video  Conclusion   COORDINATES CONVERSION: FROM GPS TO UTM In this exercise, it is given GPS coordinates from boat position and the estimated survivors positions. Using the online conversor we can get the following UTM coordinates:  Boat: 40º16’48.2” N , 3º49’03.5” W   ->...
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