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acamacho.ruiz

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  • Object Detection With Sipeed MaiX Boards(Kendryte K210)

    I have planned 6 robots. And I have planed different features for them, some of hardware, sensors, others in AI...which each one is a whole project itself. In the project that you helped me, it is a AI project to incorporate it in at least three robots in LV1 and in other 3 in a LV2 with more features.The LV1 is a Inference model to detect different kind of ground surface , as parquet, carpet,gravel, sand,grass,high grass....and give them a condition of obstacule or drivable surface in the navigation stack of ROS. The LV2 go further, and with a exotic senors+ML will make semantic slam, avoiding the segmentantion (via computer vision) and object classification (CNN) avoiding the heaviest duty of the semantic part, and can bring semantic slam to low power SoC as rpi4, upboard., Nano and t...

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    I have planned 6 robots. And I have planed different features for them, some of hardware, sensors, others in AI...which each one is a whole project itself. In the project that you helped me, it is a AI project to incorporate it in at least three robots in LV1 and in other 3 in a LV2 with more features.The LV1 is a Inference model to detect different kind of ground surface , as parquet, carpet,gravel, sand,grass,high grass....and give them a condition of obstacule or drivable surface in the navigation stack of ROS. The LV2 go further, and with a exotic senors+ML will make semantic slam, avoiding the segmentantion (via computer vision) and object classification (CNN) avoiding the heaviest duty of the semantic part, and can bring semantic slam to low power SoC as rpi4, upboard., Nano and the small robots , no just to autonomous cars or 100k drones

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  • Object Detection With Sipeed MaiX Boards(Kendryte K210)

    Just tell you a really BIG thank you for your fantastic answer, and congrats you by another great tutorial.Thanks to you I found a way to get all I needed for my robots (CNN object detection and send it via UART to a SoC) and with ROS link the coordenates to a Point cloud (PCL) to give a 3d ubication of the object and can get semantic slam.I will need learn everything from 0 to get it, from make my own model, to learn micropytnon(openmv implementation included),and make my own ros node for openmv/maix communication,(I have planned fork and modify one from openmv) further the PCL and semantic slam implementation.With this I will have entertaiment learning for probably years,really I dont care if somebody all thanks to you.The part of "with some tinkering it should be possible to d...

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    Just tell you a really BIG thank you for your fantastic answer, and congrats you by another great tutorial.Thanks to you I found a way to get all I needed for my robots (CNN object detection and send it via UART to a SoC) and with ROS link the coordenates to a Point cloud (PCL) to give a 3d ubication of the object and can get semantic slam.I will need learn everything from 0 to get it, from make my own model, to learn micropytnon(openmv implementation included),and make my own ros node for openmv/maix communication,(I have planned fork and modify one from openmv) further the PCL and semantic slam implementation.With this I will have entertaiment learning for probably years,really I dont care if somebody all thanks to you.The part of "with some tinkering it should be possible to do pose detection and image segmentation(for example for monocular depth estimation)" sounds a lot similar to what I have planned to get semantic slam (include segmentation), any further information about this should be great.

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  • acamacho.ruiz followed DmitryM86 months ago
      • Object Detection With Sipeed MaiX Boards(Kendryte K210)
      • ROS Melodic on Raspberry Pi 4[Debian Buster] + RPLIDAR A1M8
      • Image Recognition With Sipeed MaiX and Arduino IDE/Micropython
  • ROS Melodic on Raspberry Pi 4[Debian Buster] + RPLIDAR A1M8

    Thank you for you help, I will check out your advice. Wasn't my intention you spend your free time in advicee, but if you decide make that tutorial really should be great, to give support that hardware

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