I am trying to use tfluna lidar v1.2 sensor with Jetson nano. However, when I try to communicate with the sensor with I2C, the address does not appear. When I use the i2cdetect -y -r 1 command, nothing shows up.
hello serdarkaraceylan703,
may I know what’s your hardware setups, are you using 40-pin expansion header?
$ sudo apt-cache show nvidia-jetpack
[sudo] password for karaceylan:
Package: nvidia-jetpack
Version: 4.6.3-b17
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0), nvidia-cuda (= 4.6.3-b17), nvidia-tensorrt (= 4.6.3-b17), nvidia-nsight-sys (= 4.6.3-b17), nvidia-cudnn8 (= 4.6.3-b17), nvidia-opencv (= 4.6.3-b17), nvidia-container (= 4.6.3-b17), nvidia-vpi (= 4.6.3-b17)
Homepage: Jetson - Embedded AI Computing Platform | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.3-b17_arm64.deb
Size: 29368
SHA256: 694254a8667ebbf13852548bdd13a5b8ae61481ac059845b706398eefdcb9e01
SHA1: 67140fc8463ec61fd69352b225244b639c799edd
MD5sum: afa1382b6caded6b736d494fc481bab4
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Version: 4.6.2-b5
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.6.2-b5), nvidia-opencv (= 4.6.2-b5), nvidia-cudnn8 (= 4.6.2-b5), nvidia-tensorrt (= 4.6.2-b5), nvidia-visionworks (= 4.6.2-b5), nvidia-container (= 4.6.2-b5), nvidia-vpi (= 4.6.2-b5), nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0)
Homepage: Jetson - Embedded AI Computing Platform | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.2-b5_arm64.deb
Size: 29378
SHA256: 925f4abff97e6024d86cff3b9e132e7c7554d05fb83590487381b7e925d5b2bb
SHA1: e3ef727e87df5c331aece34508c110d57d744fe9
MD5sum: 7cb2e387af41bc8143ac7b6525af7794
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Version: 4.6.1-b110
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.6.1-b110), nvidia-opencv (= 4.6.1-b110), nvidia-cudnn8 (= 4.6.1-b110), nvidia-tensorrt (= 4.6.1-b110), nvidia-visionworks (= 4.6.1-b110), nvidia-container (= 4.6.1-b110), nvidia-vpi (= 4.6.1-b110), nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0)
Homepage: Jetson - Embedded AI Computing Platform | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.1-b110_arm64.deb
Size: 29366
SHA256: acfd9e75af780eab165361d61de4b4fe4974890864fe191060b402ac4c2f54d5
SHA1: a016568ac53705acc145a9f7e60505707bea259f
MD5sum: 79be976b184a8c885bd9169ea5b7fb7b
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
I can’t use 40 pin expansion header. Because Jetson-io.py is not working.
hello serdarkaraceylan703,
you may check release tag $ cat /etc/nv_tegra_release for your current release version.
so, what’s your hardware setups to wire the tfluna lidar sensor.
$ cat /etc/nv_tegra_release
R32 (release), REVISION: 7.3, GCID: 31982016, BOARD: t210ref, EABI: aarch64, DATE: Tue Nov 22 17:30:08 UTC 2022
$ sudo i2cdetect -y -r 1
[sudo] password for karaceylan:
0 1 2 3 4 5 6 7 8 9 a b c d e f
00: – – – – – – – – – – – – –
10: – – – – – – – – – – – – – – – –
20: – – – – – – – – – – – – – – – –
30: – – – – – – – – – – – – – – – –
40: – – – – – – – – – – – – – – – –
50: – – – – – – – – – – – – – – – –
60: – – – – – – – – – – – – – – – –
70: – – – – – – – –
which pin you’ve connected to communicate with the sensor
3 → SDA
5 → SCL
GNG → I2C Mode
hello serdarkaraceylan703,
please see-also Jetson Nano Developer Kit User Guide, may I know which connector you’re used.
you may also check Jetson Nano Product Design Guide for [Figure 11-1. I2C Connections]. please check you’re using correct pin connections to your I2C devices.
I’m pretty sure I made the pin connections correctly. When I connect the sensor to uart communication, I see it working. However, when I try to communicate with I2C, I cannot see the address on the map.
Also, why the Jetson-io.py file is not working, I still couldn’t find a solution. Even though I’ve gone through the past discussion threads and tried the implemented solutions, jetson-io.py still doesn’t work.
are you using a customize board? Jetson-IO it only works with developer kits.
hello serdarkaraceylan703,
what’s the storage types? for example, is this using SD card, or it’s using an internal eMMC version?
FYI.
Jetson-IO is for development purpose use only - so it only enable for Module with SD version.
Module with eMMC version is for production purpose, and will be used on customized carrier board. The official procedure is to use pinmux table to make any change.
I am using sd card
hello serdarkaraceylan703,
may I know what happened by running below?
$ cd /opt/nvidia/jetson-io/
$ sudo python jetson-io.py
I sent the Jetson Nano to the place where I bought it. They said they would work on it. As soon as I get the Jetson Nano, I will implement the codes.
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