cogniteam - User contributions [en]

Category:HamsterV8

2022-06-08T07:28:09Z

Ariy:

[[[File:HamsterV7.jpg|thumb]]
== Hamster V8 based on Raspberry PI 4 Model B ==

Features :
* Raspberry PI 4 Model B
* Intel RealSense D435i
* 2D Lidar
* Motor encoder
* ROS1 and ROS2
* Cloud connected with [https://www.cognimbus.com Nimbus]

=== Configuration ===

* Ubuntu Server 20.04.3 LTS for Raspberry PI 4 Model B:
Image that you need for Hamster V8 is [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/raspberry_pi_4_4gb&fileid=153865 here]

=== Connections ===

<big>Raspberry PI 4 Model B:
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:RP-RASPBERRY-PI-4-B-1GB_Raspberry_Pi_4_1800x1800.jpg|
</gallery>

<big>Raspberry PI 4 ports:
</big>
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:raspberry-4-modele-b-4go.jpg|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

<big>Hamster LLC:
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:LLC.jpeg|
File:asdasdadasdasdsa.jpeg|
</gallery>

<big>USB-C Power connection to Raspberry PI and power connection to LIDAR with cabels from Hamster LLC :
</big>
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:Untitled 1.jpeg|
</gallery>

== Components in Hamster V8 ==

<big>Intel® RealSense™ D435i Depth Camera</big>

Intel® RealSense™ depth camera D435i combines the robust depth sensing capabilities of the D435 with the addition of an inertial measurement unit (IMU).
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:stereo_DT_d435_front-crop1a.png|
</gallery>

<big>RPLIDAR A2</big>

The core of RPLIDAR A2 runs clockwise to perform a 360 degree omnidirectional laser range scanning
for its surrounding environment and then generate an outline map for the environment.

<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:summary-section5.jpg|
</gallery>

== Media ==
* [[HamsterPython| Programming Hamsters with Python and ROS]]
* [https://cloud.cogni.io/index.php/s/6q1j9J8mRNLAkFP Hamster Vision ROS bag file]
* [https://wiki.up-community.org/Hardware_Specification_UP2 Up Squared wiki]

==Hamster V8 wireless network==

=== Router ===
* SSID 2.4Ghz/5.0Ghz: hamster_net
* Password: hamsterHAMSTER
* Network: 10.0.2.0
* Netmask: 255.255.255.0
* Gateway: 10.0.2.138

=== Hamster ===

* User = ubuntu
* Password = raspiRASPI
* IP = 10.0.2.* (*depends on number on your Hamster V8)

Category:HamsterV8

2022-06-08T07:27:28Z

Ariy:

[[[File:HamsterV7.jpg|thumb]]
== Hamster V8 based on Raspberry PI 4 Model B ==

Features :
* Raspberry PI 4 Model B
* Intel RealSense D435i
* 2D Lidar
* Motor encoder
* ROS1 and ROS2
* Cloud connected with [https://www.cognimbus.com Nimbus]

=== Configuration ===

* Ubuntu Server 20.04.3 LTS for Raspberry PI 4 Model B:
Image that you need for Hamster V8 is [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/raspberry_pi_4_4gb&fileid=153865 here]

=== Connections ===

<big>Raspberry PI 4 Model B:
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:RP-RASPBERRY-PI-4-B-1GB_Raspberry_Pi_4_1800x1800.jpg|
</gallery>

<big>Raspberry PI 4 ports:
</big>
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:raspberry-4-modele-b-4go.jpg|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

<big>Hamster LLC:
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:LLC.jpeg|
File:asdasdadasdasdsa.jpeg|
</gallery>

<big>USB-C Power connection to Raspberry PI and power connection to LIDAR with cabels from Hamster LLC :
</big>
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:Untitled 1.jpeg|
</gallery>

== Components in Hamster V8 ==

<big>Intel® RealSense™ D435i Depth Camera</big>

Intel® RealSense™ depth camera D435i combines the robust depth sensing capabilities of the D435 with the addition of an inertial measurement unit (IMU).
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:stereo_DT_d435_front-crop1a.png|
</gallery>

<big>RPLIDAR A2</big>

The core of RPLIDAR A2 runs clockwise to perform a 360 degree omnidirectional laser range scanning
for its surrounding environment and then generate an outline map for the environment.

<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:summary-section5.jpg|
</gallery>

== Media ==
* [[HamsterPython| Programming Hamsters with Python and ROS]]
* [https://cloud.cogni.io/index.php/s/6q1j9J8mRNLAkFP Hamster Vision ROS bag file]
* [https://wiki.up-community.org/Hardware_Specification_UP2 Up Squared wiki]

==Hamster V8 wireless network==

===Router===
* SSID 2.4Ghz/5.0Ghz: hamster_net
* Password: hamsterHAMSTER
* Network: 10.0.2.0
* Netmask: 255.255.255.0
* Gateway: 10.0.2.138

===Hamster===

* User = ubuntu
* Password = raspiRASPI
* IP = 10.0.2.* (*depends on number on your Hamster V8)

Category:HamsterV8

2022-06-08T07:26:43Z

Ariy:

[[[File:HamsterV7.jpg|thumb]]
== Hamster V8 based on Raspberry PI 4 Model B ==

Features :
* Raspberry PI 4 Model B
* Intel RealSense D435i
* 2D Lidar
* Motor encoder
* ROS1 and ROS2
* Cloud connected with [https://www.cognimbus.com Nimbus]

=== Configuration ===

* Ubuntu Server 20.04.3 LTS for Raspberry PI 4 Model B:
Image that you need for Hamster V8 is [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/raspberry_pi_4_4gb&fileid=153865 here]

=== Connections ===

<big>Raspberry PI 4 Model B:
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:RP-RASPBERRY-PI-4-B-1GB_Raspberry_Pi_4_1800x1800.jpg|
</gallery>

<big>Raspberry PI 4 ports:
</big>
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:raspberry-4-modele-b-4go.jpg|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

<big>Hamster LLC:
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:LLC.jpeg|
File:asdasdadasdasdsa.jpeg|
</gallery>

<big>USB-C Power connection to Raspberry PI and power connection to LIDAR with cabels from Hamster LLC :
</big>
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:Untitled 1.jpeg|
</gallery>

== Components in Hamster V8 ==

<big>Intel® RealSense™ D435i Depth Camera</big>

Intel® RealSense™ depth camera D435i combines the robust depth sensing capabilities of the D435 with the addition of an inertial measurement unit (IMU).
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:stereo_DT_d435_front-crop1a.png|
</gallery>

<big>RPLIDAR A2</big>

The core of RPLIDAR A2 runs clockwise to perform a 360 degree omnidirectional laser range scanning
for its surrounding environment and then generate an outline map for the environment.

<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:summary-section5.jpg|
</gallery>

== Media ==
* [[HamsterPython| Programming Hamsters with Python and ROS]]
* [https://cloud.cogni.io/index.php/s/6q1j9J8mRNLAkFP Hamster Vision ROS bag file]
* [https://wiki.up-community.org/Hardware_Specification_UP2 Up Squared wiki]

==Hamster V8 wireless network==

==Router==
* SSID 2.4Ghz/5.0Ghz: hamster_net
* Password: hamsterHAMSTER
* Network: 10.0.2.0
* Netmask: 255.255.255.0
* Gateway: 10.0.2.138

==Hamster==

* User = ubuntu
* Password = raspiRASPI
* IP = 10.0.2.* (*depends on number on your Hamster V8)

Category:HamsterV8

2022-06-08T07:26:15Z

Ariy:

[[[File:HamsterV7.jpg|thumb]]
== Hamster V8 based on Raspberry PI 4 Model B ==

Features :
* Raspberry PI 4 Model B
* Intel RealSense D435i
* 2D Lidar
* Motor encoder
* ROS1 and ROS2
* Cloud connected with [https://www.cognimbus.com Nimbus]

=== Configuration ===

* Ubuntu Server 20.04.3 LTS for Raspberry PI 4 Model B:
Image that you need for Hamster V8 is [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/raspberry_pi_4_4gb&fileid=153865 here]

=== Connections ===

<big>Raspberry PI 4 Model B:
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:RP-RASPBERRY-PI-4-B-1GB_Raspberry_Pi_4_1800x1800.jpg|
</gallery>

<big>Raspberry PI 4 ports:
</big>
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:raspberry-4-modele-b-4go.jpg|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

<big>Hamster LLC:
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:LLC.jpeg|
File:asdasdadasdasdsa.jpeg|
</gallery>

<big>USB-C Power connection to Raspberry PI and power connection to LIDAR with cabels from Hamster LLC :
</big>
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:Untitled 1.jpeg|
</gallery>

== Components in Hamster V8 ==

<big>Intel® RealSense™ D435i Depth Camera</big>

Intel® RealSense™ depth camera D435i combines the robust depth sensing capabilities of the D435 with the addition of an inertial measurement unit (IMU).
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:stereo_DT_d435_front-crop1a.png|
</gallery>

<big>RPLIDAR A2</big>

The core of RPLIDAR A2 runs clockwise to perform a 360 degree omnidirectional laser range scanning
for its surrounding environment and then generate an outline map for the environment.

<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:summary-section5.jpg|
</gallery>

== Media ==
* [[HamsterPython| Programming Hamsters with Python and ROS]]
* [https://cloud.cogni.io/index.php/s/6q1j9J8mRNLAkFP Hamster Vision ROS bag file]
* [https://wiki.up-community.org/Hardware_Specification_UP2 Up Squared wiki]

==Hamster V8 wireless network==

==Router==
* SSID 2.4Ghz/5.0Ghz: hamster_net
* Password: hamsterHAMSTER
* Network: 10.0.2.0
* Netmask: 255.255.255.0
* Gateway: 10.0.2.138

==Hamster==

* User = ubuntu
* Password = raspiRASPI
* IP = 10.0.2.* (*depends on number on your Hamster V8)

Category:HamsterV8

2022-06-08T07:25:06Z

Ariy:

[[[File:HamsterV7.jpg|thumb]]
== Hamster V8 based on Raspberry PI 4 Model B ==

Features :
* Raspberry PI 4 Model B
* Intel RealSense D435i
* 2D Lidar
* Motor encoder
* ROS1 and ROS2
* Cloud connected with [https://www.cognimbus.com Nimbus]

=== Configuration ===

* Ubuntu Server 20.04.3 LTS for Raspberry PI 4 Model B:
Image that you need for Hamster V8 is [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/raspberry_pi_4_4gb&fileid=153865 here]

=== Connections ===

<big>Raspberry PI 4 Model B:
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:RP-RASPBERRY-PI-4-B-1GB_Raspberry_Pi_4_1800x1800.jpg|
</gallery>

<big>Raspberry PI 4 ports:
</big>
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:raspberry-4-modele-b-4go.jpg|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

<big>Hamster LLC:
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:LLC.jpeg|
File:asdasdadasdasdsa.jpeg|
</gallery>

<big>USB-C Power connection to Raspberry PI and power connection to LIDAR with cabels from Hamster LLC :
</big>
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:Untitled 1.jpeg|
</gallery>

== Components in Hamster V8 ==

<big>Intel® RealSense™ D435i Depth Camera</big>

Intel® RealSense™ depth camera D435i combines the robust depth sensing capabilities of the D435 with the addition of an inertial measurement unit (IMU).
<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:stereo_DT_d435_front-crop1a.png|
</gallery>

<big>RPLIDAR A2</big>

The core of RPLIDAR A2 runs clockwise to perform a 360 degree omnidirectional laser range scanning
for its surrounding environment and then generate an outline map for the environment.

<gallery widths=300px heights=350px mode="packed-hover margin-right" border=none>
File:summary-section5.jpg|
</gallery>

== Media ==
* [[HamsterPython| Programming Hamsters with Python and ROS]]
* [https://cloud.cogni.io/index.php/s/6q1j9J8mRNLAkFP Hamster Vision ROS bag file]
* [https://wiki.up-community.org/Hardware_Specification_UP2 Up Squared wiki]

==Hamster V8 wireless network==

===Router===
* SSID 2.4Ghz/5.0Ghz: hamster_net
* Password: hamsterHAMSTER
* Network: 10.0.2.0
* Netmask: 255.255.255.0
* Gateway: 10.0.2.138

===Hamster===

* User = ubuntu
* Password = raspiRASPI
* IP = 10.0.2.* (*depends on number on your Hamster V8)

Category:Lynx

2021-12-16T12:50:07Z

Ariy:

== '''Lynx is an R&D outdoor robot with all-terrain capabilities.''' ==

<gallery widths=450px heights=450px mode="packed-hover margin-right" border=none>
File:WhatsApp Image 2021-12-14 at 12.39.14.jpeg|
</gallery>

==='''<big>Our Lynx come with Nimbus already on board.</big>'''===

<big>It fully supports ROS and Nimbus and arrives with the necessary sensors for off-road autonomy. Start your outdoor journey using Lynx and Nimbus and you will develop and monitor your robot anywhere.
</big>

<gallery widths=450px heights=450px mode="packed-hover margin-right" border=none>
File:WhatsApp Image 2021-12-14 at 12.40.12.jpeg|
</gallery>

<big>Lynx allows you to implement and run R&D for indoor robots with vision-based applications (deep neural network).
</big>
===It includes the following main sensors:===

* <big>2D (360 degree) Lidar</big>

* <big>Depth camera (Intel's realsense D435i)</big>

* <big>IMU (inside the depth camera)</big>

===Computational power:===

* <big>AAEON's BOXER-8240AI (AGX Xavier)</big>

===Platform:===

<big>Weight: 60 Kg</big>

<big>Max speed: 40 Km/h</big>

<big>Long lasting battery</big>

<big>Over 120 Kg payload</big>

<big>Lynx is an R&D autonomous all terrain vehicle (ATV) capable of powering, carrying and interfacing various payloads.

Lynx is capable of powerful computations, including Mapping (SLAM), Localization, Path Planning, Exploration, Waypoint Driving, Obstacle Avoidance and classification using HW supported VPU - all running on board the robot.

For outdoor environments, Lynx is equipped with GPS, a motor encoder and an IMU which enables high location accuracy and PID control for travelling at up to 40 km/h.
</big>

<gallery widths=450px heights=450px mode="packed-hover margin-right" border=none>
File:Screenshot from 2021-12-16 14-48-06.png|</gallery>

File:Screenshot from 2021-12-16 14-48-06.png

2021-12-16T12:48:44Z

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Category:Lynx

2021-12-16T12:46:39Z

Ariy:

Category:Lynx

2021-12-16T12:11:02Z

Ariy: Created page with "== '''Lynx is an R&D outdoor robot with all-terrain capabilities.''' == <gallery widths=450px heights=450px mode="packed-hover margin-right" border=none> File:WhatsApp Ima..."

File:WhatsApp Image 2021-12-14 at 12.40.12.jpeg

2021-12-16T11:53:48Z

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File:WhatsApp Image 2021-12-14 at 12.39.39.jpeg

2021-12-16T11:53:47Z

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File:WhatsApp Image 2021-12-14 at 12.39.14.jpeg

2021-12-16T11:53:46Z

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Cogniteam/Nvidia

2021-12-15T10:19:41Z

Ariy:

== About NVIDIA ==

For more than 25 years, NVIDIA has been a world leader in vision computing solutions. NVIDIA GPUs are used in a variety of deep learning, artificial intelligence, and accelerated analytics applications that leverage artificial intelligence to approach the world’s most challenging problems.

[https://developer.nvidia.com/embedded-computing?ncid=partn-234961#cid=em16_partn_en-us Visit the NVIDIA website]

== Platforms ==
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

Category:HamsterProKit

2021-12-06T13:41:34Z

Ariy:

=== AAEON Pro Kit support page ===

[[File:Charger_LLC_Battery_rev2.jpg|800px]]
[[File:ProKitLLC.png|600px]]
== Landing page ==
* [https://up-board.org/up-squared-robomaker-pro-kit/]

==3rd party things need to know to work with kit==

* ROS general information: [http://wiki.ros.org/ROS/Introduction WHAT IS ROS]

* ROS2 general information: [https://index.ros.org/doc/ros2/ ROS2]

* RVIZ - instrument for visualization: [http://wiki.ros.org/rviz/UserGuide RVIZ]

== Kit prerequisite (not included in the kit) ==
* Lipo battery with T connector 7.4V 2 cell.
* Battery charger

===1. Connecting all parts within the kit ===
* Use the LLC cable (in the picture) to both monitor and charge the battery
* Port 8 can be used to charge the Lipo Battery
* Port 9 should connect the the Lipo battery balancer (JST connector)
* Port 7 should connect to the LLC board
* Red T connector (rightmost on the picture)
* Connect the Up Squared board to the LLC as shown in the picture
* TX/RX should be connected to GPIO ports
* Power should be connected through DC connector
* Connect the MX2 wifi module
* Connect the two WIFI antennas using the SMT connector to the integrated chip
* Connect the Movidius chip using the PCI connector
* Connect the D435i camera to a USB3 Port using the cable

'''Note: Camera D435i must be already updated with latest firmware and have calibrated IMU. Visit official site for more information.'''

===2. Run installation script ===

Internet connection requires

<code>sudo wget https://cloud.cogni.io/index.php/s/9Lde7aBNHfyQM6K -O - | bash</code>

Reboot board after installation.

===3. Configure ROS IP ===

Configure IP for ROS applications:

<code>pico hamster.config</code> in home directory

Edit row with your board IP:

<code>export HAMSTER_IP=your_IP</code>

===4. Launch examples ===

'''NOTE: examples work properly just with full-connected kit, be sure you did step 1 from this page.'''

To run examples in ROS run command:

<code>ros_prokit</code>

[https://wiki.cogni.io/Category:HamsterProKit/RosExample ROS_EXAMPLES]

To run example in ROS2 run command:

<code>ros2_prokit</code>

[https://wiki.cogni.io/Category:HamsterProKit/Ros2Example ROS2_EXAMPLES]

Cogniteam/Jetson Xavier NX™ Developer Kit

2021-12-02T13:47:45Z

Ariy:

==Jetson Xavier NX™ Developer Kit==

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson_Xavier_NX-Developer_Kit-Front_Top_Right.png|
</gallery>

The NVIDIA® Jetson Xavier NX™ Developer Kit includes a power-efficient, compact Jetson Xavier NX module for AI edge devices. It benefits from new cloud-native support, and accelerates the NVIDIA software stack in as little as 10 W with more than 10x the performance of its widely adopted predecessor Jetson TX2.

For intelligent machine OEMs, start-ups and AI application developers who want to create breakthrough products, the Jetson Xavier NX Developer Kit delivers the capability to develop and test power-efficient, small form factor solutions with accurate, multi-modal AI inference.

==Image for Jetson Xavier NX™ Developer Kit [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/jetson_xavier&fileid=153860 here]==

==Ports & Interfaces==

<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson-Xavier-NX-DevKit.jpg|
File:Pin1XNX-scaled.jpg|
</gallery>

* (4x) USB 3.1 A (Host)
* USB 2.0 Micro B (Device)
* (2x) MIPI CSI-2 x2 (15-position Camera Flex Connector)
* HDMI 2.0
* DisplayPort 1.4
* Gigabit Ethernet (RJ45)
* M.2 Key-E with PCIe x1 (includes 2x2 802.11ac + BT 5.0 RTL8211 module)
* M.2 Key-M NVMe with PCIe x4
* MicroSD card slot
* (2x) I2C, (2x) SPI, UART, I2S, GPIOs

==Connection with Hamster LLC – 6 (Ground), 8 (UART1_TXD), 10 (UART1_RXD):==
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:pinout jetson.png|
</gallery>

==Network connection to Hamster V7 [https://wiki.cogni.io/Category:HamsterV7N here]==

Category:HamsterV6

2021-12-02T13:45:14Z

Ariy:

{{DISPLAYTITLE:Hamster V6}}

[[Category:Hamster]]
[[File:HamsterV5.png|200px|thumb|HamsterV6]]
[[File:HamsterV5front.png|200px|thumb|HamsterV6]]

<big>The Hamster robot is a robotic research platform focused on autonomy. Hamster can localize and map indoor areas, stream video and has full ROS support for developers.
</big>
<big>The hamster platform arrives with various components pre-installed:
</big>
* A2 6-10m range 360 Lidar supported by ROS
* An HD capable camera supported by ROS
* Raspberry Pi 3 Model B+ boards with Linux (Ubuntu 20.04) and ROS Noetic
* A Low Level controller with dedicated hardware for power distribution and monitoring

=== Configuration of Raspberry PI 3 Model B+:===
Ubuntu Server 20.04.3 LTS:
Image that you need for Hamster V6 is [https://cloud.cogni.io/index.php/apps/files?dir=/hamster_imgs/raspberry_pi_3_b_plus&fileid=153863 here]

<big>Raspberry Pi 3 Model B+</big>

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:raspi3_1.jpg|
File:raspi3.jpg|
</gallery>

<big>Raspberry Pi 3 Model B+ ports</big>

<gallery widths=450px heights=350px mode="packed-hover margin-right" border=none>
File:Screenshot from 2021-12-02 15-38-56.png|
</gallery>

<big>Connection with Hamster LLC – '''6 (Ground), 8 (UART0_TXD), 10 (UART0_RXD)''':
</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:rpiAp.jpg|
</gallery>

File:Raspi3 1.jpg

2021-12-02T13:42:10Z

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File:Raspi3.jpg

2021-12-02T13:42:09Z

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File:Screenshot from 2021-12-02 15-38-56.png

2021-12-02T13:39:30Z

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Cogniteam/AAEON

2021-12-02T13:24:20Z

Ariy:

== Platforms ==
* [[Cogniteam/UpSquared|UP Squared Developer Board]]

Cogniteam

2021-12-02T13:23:51Z

Ariy:

Welcome to Cogniteam's wiki

[[File:Cogniteam - our team.jpg|thumb|Cogniteam]]

Visit our website to hear about exciting new products
[http://www.cogniteam.com Cogniteam]

This wiki purpose is to give support for a wide range of products
and help back the community in a range of development issues we encounter daily.

== Partners ==
* [[Cogniteam/ADLink|ADLink]]
* [[Cogniteam/AAEON|AAEON]]
* [[Cogniteam/Nvidia|Nvidia]]

== Product support pages ==
* [[Cogniteam/ROSCUBE|ROSCUBE]]
* [[Cogniteam/UpSquared|Up Squared]]
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

== Our recent talks at meetups and conferences ==
* Israel Robotics Meetup #7 - Introduction to SLAM | Dr. Yehuda Elmaliah (CEO @ Cogniteam)
[[File:YehudaMeetup7.png|thumb]] [[https://www.youtube.com/watch?v=E9IpPfwIyJI]]

* Robotic Meetup #1- Developing Autonomous Things | Ari Yakir (VP R&D @ Cogniteam)
[[File:AriYakirMeetup.mp4.png|thumb]] [[https://www.youtube.com/watch?v=V8rHo_QpWTU]]

* Robotics Development and Fleet Management on Cogniteam's Nimbus Cloud Platform & NVIDIA Isaac SDK | Ari Yakir (VP R&D @ Cogniteam)
[[File:AAEON_Nimbus_webinar.png|thumb|AAEON Nimbus Webinar]] [[https://www.youtube.com/watch?v=TfuFyRoPL7Y&ab_channel=AAEONEurope]]

== For developers ==
* [[Cogniteam/CodeConvention|Code conventions]]

== Clients ==
* [[Debian_repository|Cogniteam APT Repository]]

Cogniteam/AAEON

2021-12-02T13:23:25Z

Ariy:

== Platforms ==
* [[Cogniteam/Up Squared|UP Squared Developer Board]]

Cogniteam

2021-12-02T13:23:13Z

Ariy:

Welcome to Cogniteam's wiki

[[File:Cogniteam - our team.jpg|thumb|Cogniteam]]

Visit our website to hear about exciting new products
[http://www.cogniteam.com Cogniteam]

This wiki purpose is to give support for a wide range of products
and help back the community in a range of development issues we encounter daily.

== Partners ==
* [[Cogniteam/ADLink|ADLink]]
* [[Cogniteam/AAEON|AAEON]]
* [[Cogniteam/Nvidia|Nvidia]]

== Product support pages ==
* [[Cogniteam/ROSCUBE|ROSCUBE]]
* [[Cogniteam/Up Squared|Up Squared]]
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

== Our recent talks at meetups and conferences ==
* Israel Robotics Meetup #7 - Introduction to SLAM | Dr. Yehuda Elmaliah (CEO @ Cogniteam)
[[File:YehudaMeetup7.png|thumb]] [[https://www.youtube.com/watch?v=E9IpPfwIyJI]]

* Robotic Meetup #1- Developing Autonomous Things | Ari Yakir (VP R&D @ Cogniteam)
[[File:AriYakirMeetup.mp4.png|thumb]] [[https://www.youtube.com/watch?v=V8rHo_QpWTU]]

* Robotics Development and Fleet Management on Cogniteam's Nimbus Cloud Platform & NVIDIA Isaac SDK | Ari Yakir (VP R&D @ Cogniteam)
[[File:AAEON_Nimbus_webinar.png|thumb|AAEON Nimbus Webinar]] [[https://www.youtube.com/watch?v=TfuFyRoPL7Y&ab_channel=AAEONEurope]]

== For developers ==
* [[Cogniteam/CodeConvention|Code conventions]]

== Clients ==
* [[Debian_repository|Cogniteam APT Repository]]

Cogniteam/AAEON

2021-12-02T13:22:48Z

Ariy: Created page with "== Platforms == * UP Squared Developer Board"

== Platforms ==
* [[Cogniteam/UpSquared|UP Squared Developer Board]]

Cogniteam

2021-12-02T13:21:10Z

Ariy:

Welcome to Cogniteam's wiki

[[File:Cogniteam - our team.jpg|thumb|Cogniteam]]

Visit our website to hear about exciting new products
[http://www.cogniteam.com Cogniteam]

This wiki purpose is to give support for a wide range of products
and help back the community in a range of development issues we encounter daily.

== Partners ==
* [[Cogniteam/ADLink|ADLink]]
* [[Cogniteam/AAEON|AAEON]]
* [[Cogniteam/Nvidia|Nvidia]]

== Product support pages ==
* [[Cogniteam/ROSCUBE|ROSCUBE]]
* [[Cogniteam/UpSquared|UpSquared]]
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

== Our recent talks at meetups and conferences ==
* Israel Robotics Meetup #7 - Introduction to SLAM | Dr. Yehuda Elmaliah (CEO @ Cogniteam)
[[File:YehudaMeetup7.png|thumb]] [[https://www.youtube.com/watch?v=E9IpPfwIyJI]]

* Robotic Meetup #1- Developing Autonomous Things | Ari Yakir (VP R&D @ Cogniteam)
[[File:AriYakirMeetup.mp4.png|thumb]] [[https://www.youtube.com/watch?v=V8rHo_QpWTU]]

* Robotics Development and Fleet Management on Cogniteam's Nimbus Cloud Platform & NVIDIA Isaac SDK | Ari Yakir (VP R&D @ Cogniteam)
[[File:AAEON_Nimbus_webinar.png|thumb|AAEON Nimbus Webinar]] [[https://www.youtube.com/watch?v=TfuFyRoPL7Y&ab_channel=AAEONEurope]]

== For developers ==
* [[Cogniteam/CodeConvention|Code conventions]]

== Clients ==
* [[Debian_repository|Cogniteam APT Repository]]

Cogniteam

2021-12-02T13:18:10Z

Ariy:

Welcome to Cogniteam's wiki

[[File:Cogniteam - our team.jpg|thumb|Cogniteam]]

Visit our website to hear about exciting new products
[http://www.cogniteam.com Cogniteam]

This wiki purpose is to give support for a wide range of products
and help back the community in a range of development issues we encounter daily.

== Partners ==
* [[Cogniteam/ADLink|ADLink]]
* [[Cogniteam/Nvidia|Nvidia]]

== Product support pages ==
* [[Cogniteam/ROSCUBE|ROSCUBE]]
* [[Cogniteam/UpSquared|UpSquared]]
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

== Our recent talks at meetups and conferences ==
* Israel Robotics Meetup #7 - Introduction to SLAM | Dr. Yehuda Elmaliah (CEO @ Cogniteam)
[[File:YehudaMeetup7.png|thumb]] [[https://www.youtube.com/watch?v=E9IpPfwIyJI]]

* Robotic Meetup #1- Developing Autonomous Things | Ari Yakir (VP R&D @ Cogniteam)
[[File:AriYakirMeetup.mp4.png|thumb]] [[https://www.youtube.com/watch?v=V8rHo_QpWTU]]

* Robotics Development and Fleet Management on Cogniteam's Nimbus Cloud Platform & NVIDIA Isaac SDK | Ari Yakir (VP R&D @ Cogniteam)
[[File:AAEON_Nimbus_webinar.png|thumb|AAEON Nimbus Webinar]] [[https://www.youtube.com/watch?v=TfuFyRoPL7Y&ab_channel=AAEONEurope]]

== For developers ==
* [[Cogniteam/CodeConvention|Code conventions]]

== Clients ==
* [[Debian_repository|Cogniteam APT Repository]]

Cogniteam/UpSquared

2021-12-02T13:07:09Z

Ariy:

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
File:up-squared-board-back-io-v2.png|
</gallery>

<big>Connection with Hamster LLC – 6 (Ground), 8 (GPIO14-UART0_TXD), 10 (GPIO15-UART0_RXD):</big>
<gallery widths=700px heights=350px mode="packed-hover margin-right" border=none>
File:aaeon_up_40pin_expansion_pinout.jpg|
</gallery>

<big><big>Connection and installation for [https://wiki.cogni.io/Category:HamsterProKit Hamster ProKit UP Squared here].</big>

Cogniteam/UpSquared

2021-12-02T13:04:05Z

Ariy:

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
File:up-squared-board-back-io-v2.png|
</gallery>

<big>Connection with Hamster LLC – 6 (Ground), 8 (GPIO14-UART0_TXD), 10 (GPIO15-UART0_RXD):</big>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:aaeon_up_40pin_expansion_pinout.jpg|
</gallery>

<big><big>Connection and installation for [https://wiki.cogni.io/Category:HamsterProKit Hamster ProKit UP Squared here].</big>

File:Aaeon up 40pin expansion pinout.jpg

2021-12-02T13:01:43Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

Cogniteam/Jetson Xavier NX™ Developer Kit

2021-12-02T12:56:52Z

Ariy:

==Jetson Xavier NX™ Developer Kit==

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson_Xavier_NX-Developer_Kit-Front_Top_Right.png|
</gallery>

The NVIDIA® Jetson Xavier NX™ Developer Kit includes a power-efficient, compact Jetson Xavier NX module for AI edge devices. It benefits from new cloud-native support, and accelerates the NVIDIA software stack in as little as 10 W with more than 10x the performance of its widely adopted predecessor Jetson TX2.

For intelligent machine OEMs, start-ups and AI application developers who want to create breakthrough products, the Jetson Xavier NX Developer Kit delivers the capability to develop and test power-efficient, small form factor solutions with accurate, multi-modal AI inference.

<big>Image for Jetson Xavier NX™ Developer Kit [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/jetson_xavier&fileid=153860 here]</big>

==Ports & Interfaces==

<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson-Xavier-NX-DevKit.jpg|
File:Pin1XNX-scaled.jpg|
</gallery>

* (4x) USB 3.1 A (Host)
* USB 2.0 Micro B (Device)
* (2x) MIPI CSI-2 x2 (15-position Camera Flex Connector)
* HDMI 2.0
* DisplayPort 1.4
* Gigabit Ethernet (RJ45)
* M.2 Key-E with PCIe x1 (includes 2x2 802.11ac + BT 5.0 RTL8211 module)
* M.2 Key-M NVMe with PCIe x4
* MicroSD card slot
* (2x) I2C, (2x) SPI, UART, I2S, GPIOs

==Connection with Hamster LLC – 6 (Ground), 8 (UART1_TXD), 10 (UART1_RXD):==
<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:pinout jetson.png|
</gallery>

==Network connection to Hamster V7 [https://wiki.cogni.io/Category:HamsterV7N here]==

File:Pinout jetson.png

2021-12-02T12:53:26Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

Cogniteam/Jetson Xavier NX™ Developer Kit

2021-12-02T12:45:13Z

Ariy:

=Jetson Xavier NX™ Developer Kit=

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson_Xavier_NX-Developer_Kit-Front_Top_Right.png|
</gallery>

The NVIDIA® Jetson Xavier NX™ Developer Kit includes a power-efficient, compact Jetson Xavier NX module for AI edge devices. It benefits from new cloud-native support, and accelerates the NVIDIA software stack in as little as 10 W with more than 10x the performance of its widely adopted predecessor Jetson TX2.

For intelligent machine OEMs, start-ups and AI application developers who want to create breakthrough products, the Jetson Xavier NX Developer Kit delivers the capability to develop and test power-efficient, small form factor solutions with accurate, multi-modal AI inference.

<big>Image for Jetson Xavier NX™ Developer Kit [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/jetson_xavier&fileid=153860 here]</big>

<big>Connection to Hamster V7 [https://wiki.cogni.io/Category:HamsterV7N here]</big>

=Ports & Interfaces=

<gallery widths=500px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson-Xavier-NX-DevKit.jpg|
File:Pin1XNX-scaled.jpg|
</gallery>

* (4x) USB 3.1 A (Host)
* USB 2.0 Micro B (Device)
* (2x) MIPI CSI-2 x2 (15-position Camera Flex Connector)
* HDMI 2.0
* DisplayPort 1.4
* Gigabit Ethernet (RJ45)
* M.2 Key-E with PCIe x1 (includes 2x2 802.11ac + BT 5.0 RTL8211 module)
* M.2 Key-M NVMe with PCIe x4
* MicroSD card slot
* (2x) I2C, (2x) SPI, UART, I2S, GPIOs

File:Pin1XNX-scaled.jpg

2021-12-02T12:44:04Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

File:Jetson-Xavier-NX-DevKit.jpg

2021-12-02T12:44:03Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

Cogniteam/Jetson Xavier NX™ Developer Kit

2021-12-02T12:36:06Z

Ariy:

<big><big>Jetson Xavier NX™ Developer Kit
</big>

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:Jetson_Xavier_NX-Developer_Kit-Front_Top_Right.png|
</gallery>

The NVIDIA® Jetson Xavier NX™ Developer Kit includes a power-efficient, compact Jetson Xavier NX module for AI edge devices. It benefits from new cloud-native support, and accelerates the NVIDIA software stack in as little as 10 W with more than 10x the performance of its widely adopted predecessor Jetson TX2.

For intelligent machine OEMs, start-ups and AI application developers who want to create breakthrough products, the Jetson Xavier NX Developer Kit delivers the capability to develop and test power-efficient, small form factor solutions with accurate, multi-modal AI inference.

<big>Image for Jetson Xavier NX™ Developer Kit [https://cloud.cogni.io/index.php/apps/files/?dir=/hamster_imgs/jetson_xavier&fileid=153860 here]</big>

<big>Connection to Hamster V7 [https://wiki.cogni.io/Category:HamsterV7N here]</big>

Cogniteam/Jetson Xavier NX™ Developer Kit

2021-12-02T12:32:52Z

Ariy: Created page with "<big><big>Jetson Xavier NX™ Developer Kit </big> <gallery widths=350px heights=350px mode="packed-hover margin-right" border=none> File:Jetson_Xavier_NX-Developer_Kit-Fr..."

File:Jetson Xavier NX-Developer Kit-Front Top Right.png

2021-12-02T12:30:08Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

Cogniteam/UpSquared

2021-12-02T12:25:13Z

Ariy:

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
File:up-squared-board-back-io-v2.png|
File:up-squared-io-overview-v2.png|
</gallery>

<big><big>Connection and installation for [https://wiki.cogni.io/Category:HamsterProKit Hamster ProKit UP Squared here].</big>

Cogniteam/UpSquared

2021-12-02T12:22:16Z

Ariy:

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-back-io-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-io-overview-v2.png|
</gallery>

<big><big>Connection and installation for [https://wiki.cogni.io/Category:HamsterProKit Hamster ProKit UP Squared here].</big>

Cogniteam/UpSquared

2021-12-02T12:20:34Z

Ariy:

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-back-io-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-io-overview-v2.png|
</gallery>

Connection and installation for [https://wiki.cogni.io/Category:HamsterProKit Hamster ProKit UP Squared here].

Cogniteam/UpSquared

2021-12-01T15:47:19Z

Ariy: Created page with "= UP Squared Series = UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940..."

= UP Squared Series =
UP Squared is the world’s fastest x86 pro maker board based on the latest Intel platform. The UP Squared Series is powered by Intel® Atom™ x5-E3940 and clocks up to 1.8GHz with only 4W SDP and 9.5W TDP.

Inheriting the 40-pin GP-bus from the first generation of UP, although this time controlled by Altera FPGA MAX 10, UP² (UP Squared) comes with a range of additional features. Makers will enjoy up to 8GB of RAM , up to 128 GB onboard eMMC 5.0, and more I/O ports including 3x USB 3.0, 2x USB 2.0, 2x Gigabit LAN, 1x HDMI, 1x DP, eDP, mini PCI-e/mini card SATA, M.2 2230, SATA 3.0, 2 CSI and additional 60 pin board-to-board expansion (EXHAT) with GPIO.

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-front-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-bottom-p0jetaukcsj6xvcdqlifj6taah4gfrco51wln1y60w.png|
</gallery>

= Board Details =

* UP Squared Series with Intel® Atom ™ x7-E3950, up to 2.0Ghz
* Intel® HD Graphics 500-N3350/E3940, Intel® HD Graphics 505-N4200/E3950
* 2GB/4GB/8GB LPDDR4
* 32GB/64GB/128GB eMMC
* 40 Pin I/O connector
* 60-pin EXHAT for embedded applications

<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squaredboard-front-io-v3.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-board-back-io-v2.png|
</gallery>
<gallery widths=350px heights=350px mode="packed-hover margin-right" border=none>
File:up-squared-io-overview-v2.png|
</gallery>

File:Up-squared-io-overview-v2.png

2021-12-01T15:46:45Z

Ariy: File uploaded with MsUpload

File uploaded with MsUpload

File:Up-squared-front-v2.png

2021-12-01T15:30:52Z

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Category:HamsterV8

2021-11-18T11:49:04Z

Ariy:

Cogniteam

2021-11-18T08:56:05Z

Ariy:

Welcome to Cogniteam's wiki

[[File:Cogniteam - our team.jpg|thumb|Cogniteam]]

Visit our website to hear about exciting new products
[http://www.cogniteam.com Cogniteam]

This wiki purpose is to give support for a wide range of products
and help back the community in a range of development issues we encounter daily.

== Partners ==
* [[Cogniteam/ADLink|ADLink]]
* [[Cogniteam/Nvidia|Nvidia]]
* [[Cogniteam/AAEON|AAEON]]

== Product support pages ==
* [[Cogniteam/ROSCUBE|ROSCUBE]]
* [[Cogniteam/UpSquared|UpSquared]]
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]

== Our recent talks at meetups and conferences ==
* Israel Robotics Meetup #7 - Introduction to SLAM | Dr. Yehuda Elmaliah (CEO @ Cogniteam)
[[File:YehudaMeetup7.png|thumb]] [[https://www.youtube.com/watch?v=E9IpPfwIyJI]]

* Robotic Meetup #1- Developing Autonomous Things | Ari Yakir (VP R&D @ Cogniteam)
[[File:AriYakirMeetup.mp4.png|thumb]] [[https://www.youtube.com/watch?v=V8rHo_QpWTU]]

* Robotics Development and Fleet Management on Cogniteam's Nimbus Cloud Platform & NVIDIA Isaac SDK | Ari Yakir (VP R&D @ Cogniteam)
[[File:AAEON_Nimbus_webinar.png|thumb|AAEON Nimbus Webinar]] [[https://www.youtube.com/watch?v=TfuFyRoPL7Y&ab_channel=AAEONEurope]]

== For developers ==
* [[Cogniteam/CodeConvention|Code conventions]]

== Clients ==
* [[Debian_repository|Cogniteam APT Repository]]

Cogniteam/Nvidia

2021-11-18T08:53:43Z

Ariy: Created page with "== Platforms == * Jetson Xavier NX™ Developer Kit"

== Platforms ==
* [[Cogniteam/Jetson Xavier NX™ Developer Kit|Jetson Xavier NX™ Developer Kit]]