# Hardware Options

The Kerloud UAV family provides various configurations to meet the need from different scenarios.

The overview of available options is shown in the table below.

|  ID |                                                                                   Option                                                                                  |                                                                      Main Functions                                                                     |                                                                     Potential Users                                                                     |
| :-: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------: |
|  1  |               [Kerloud Pi Outdoor](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-1.-kerloud-pi-outdoor)               |                                                              Onboard Raspberry Pi computer                                                              |                                 Users getting started with basic ROS programming in C++/python for outdoor applications                                 |
|  2  |                [Kerloud Pi Indoor](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-2.-kerloud-pi-indoor)                |                                                 Onboard Raspberry Pi computer, optical flow localization                                                |                                  Users getting started with basic ROS programming in C++/python for indoor applications                                 |
|  3  |             [Kerloud Nano Outdoor](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-3.-kerloud-nano-outdoor)             |                                                           Onboard Nvidia Jetson Nano computer                                                           |         Users getting started with deep learning software in Nvidia community, and basic ROS programming in C++/python for outdoor applications         |
|  4  | [Kerloud Nano Optical Flow Indoor](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-4.-kerloud-nano-optical-flow-indoor) |                                              Onboard Nvidia Jetson Nano computer, optical flow localization                                             |          Users getting started with deep learning software in Nvidia community, and basic ROS programming in C++/python for indoor applications         |
|  5  |          [Kerloud Nano VIO Indoor](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-5.-kerloud-nano-vio-indoor)          |                                     Onboard Nvidia Jetson Nano computer, visual-inertial odometry (VIO) localization                                    |                                    Intermediate-level users intersted in deep learning and indoor vision applications                                   |
|  6  |                 [Kerloud SLAM TX2](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-6.-kerloud-slam-tx2)                 |                       Onboard Nvidia Jetson TX2 computer, visual-inertial odometry & Simultaneous Localization and Mapping (SLAM)                       |                                         Advanced users interested in indoor SLAM and path planning applications                                         |
|  7  |               [Kerloud Optimus NX](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud300_options#option-7.-kerloud-optimus-nx)               | Onboard Nvidia Jetson NX (memory 16GB) computer, visual-inertial odometry, Ego-planner based agile flight, Simultaneous Localization and Mapping (SLAM) |                                         Advanced users interested in indoor SLAM and path planning applications                                         |
|  8  |               [Kerloud 600 Vision](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud600_options#option-1.-kerloud-600-vision)               |                                                      Onboard Nvidia Jetson Nano, obstacle avoidance                                                     |                                   Intermediate-level users interested in outdoor obstacle avoidance with depth cameras                                  |
|  9  |            [Kerloud 600 Vision 4G](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud600_options#option-2.-kerloud-600-vision-4g)            |                                           Onboard Nvidia Jetson Nano, obstacle avoidance, 4G long range flight                                          |                       Intermediate-level users interested in outdoor obstacle avoidance with depth cameras and long range flights                       |
|  10 |          [Kerloud 600 Pro Cam-Pod](https://cloudkerneltech.gitbook.io/kerlouduav/userguide/hardwareoptions/kerloud600_options#option-3.-kerloud-600-pro-cam-pod)          |                                        Onboard Nvidia Jetson Nano, obstacle avoidance, high-resolution camera pod                                       | Advanced users interested in outdoor obstacle avoidance with depth cameras, and vision applications (landing on moving platforms, visual tracking, etc) |