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SKU: 92676781605

Spektrum AR637T DSMX 6-Channel AS3X & SAFE Telemetry Receiver

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Description

Spektrum AR637T DSMX 6-Channel AS3X & SAFE Telemetry ReceiverOverview Introduction The AR637T opens up a new era in receivers that will make it easier than ever for fixed wing pilots to transform their flying experience. The AR637T receiver is full range and compatible with any DSM2 and DSMX aircraft radios. Product Features Perfect for electric park pilots to large gas models requiring 6 Channels or less Built in AS3X Stabilization System with SAFE flight envelope protection AS3X and SAFE set up through

Overview

Introduction

The AR637T opens up a new era in receivers that will make it easier than ever for fixed wing pilots to transform their flying experience. The AR637T receiver is full-range and compatible with any DSM2 and DSMX aircraft radios.

Product Features

  • Perfect for electric park pilots to large gas models requiring 6 Channels or less
  • Built in AS3X Stabilization System with SAFE flight envelope protection
  • AS3X and SAFE set up through forward programming directly from your Spektrum transmitter*
  • Ready to use with Spektrum Smart ESC for one-wire telemetry data without the need of modules, links and wires
  • Full range telemetry with integrated barometer to provide altitude and vario telemetry without additional modules
  • DSMX protocol receiver with DSM2 backwards compatibility
  • Bind button allows for easy binding and eliminates the need for bind plug
  • Streamlined, end-pin design in a lightweight hard-case
  • Expansion ports for use with SRXL2 remote receivers and telemetry sensors
  • Standard servo connectors


*Please note – Using this receiver in turbine powered aircraft models is not recommended

Product Overview

Like its predecessor, the AR637T features built in AS3X Technology, but now pilots can set up and program SAFE Technology to their aircraft. AS3X Technology (3-axis stabilization) works behind the scenes to smooth out the effects of turbulence so you enjoy a sense of stability and precision that makes it feel like you're flying a much larger, expertly tuned aircraft. SAFE Technology offers an extra level of protection so that RC flying is easier than ever before. When activated, bank and pitch limitations keep you from over-controlling and automatic self-leveling makes recovery from risky or confusing attitudes as simple as releasing the sticks. Programming and set up of AS3X and SAFE is done directly from your Spektrum transmitter* with an easy 3-step forward programming initial setup. To use SAFE and AS3X technology with the AR637T receiver, the receiver needs to be set up with a compatible Spektrum transmitter. With forward programming there is no need for apps or cables to program or make changes while at the flying field.

The AR637T features full range telemetry with an integrated barometer to provide altitude and vario telemetry data without additional sensors. Additional telemetry devices such as voltage sensors can be connected to the volt port and XBus telemetry sensors can be connected through the XBus connector. It also features an SRXL2 port for an SRXL2 Remote Receiver to add additional RF path redundancy (sold separately). An SRXL2 port is available to connect compatible devices, program and update the receiver, and bind with a traditional bind plug or connect a battery. The AR637T is compatible and ready-to-use with the Spektrum Smart ESC for even easier one-wire telemetry data. Spektrum Smart ESCs combine plug-n-play simplicity with the ability to communicate with other Smart electronics – together, creating the best-performing RC system for your model imaginable. For more information about Spektrum Smart technology please visit the Spektrum Smart Technology Page.

The AR637T receiver throttle port includes Smart Throttle. When equipped with Smart Throttle the standard servo connector delivers the throttle signal to the ESC, plus the ESC can send telemetry data back to the receiver. The throttle port will automatically detect when a Smart throttle compatible ESC is plugged in and the throttle port will begin to operate in Smart Throttle mode.

No more bind plugs! Instead, a large bind button is used to enter the bind mode. All combined the Spektrum AR637T gives you more in a 6-channel receiver than ever before, so that you can fly with the highest sense of confidence possible and have more fun.

Please Note:The DX7S and DX8 Gen 1 Spektrum Transmitters will not display Altitude or Variometer telemetry with the AR637T receiver.

 

Please Note: These transmitters do not support Forward Programming devices: DX6i, DX6G2 (EU Version), DX7, DX7S, DX7SE, DX7G2 (EU Version), DX8, Non-computer transmitters

See www.spektrumrc.com for the latest updates to your receivers and transmitters

 

AR637T Setup Series


 

AS3X® TECHNOLOGY (3-AXIS STABILIZATION)

Exclusive Spektrum™ AS3X® technology enhances flight stability by countering the effects of wind, turbulence, and other outside forces to help your aircraft fly smoothly and with precision. You’ll feel like you’re piloting an expertly tuned model that performs exactly as you want.

 

FORWARD PROGRAMMING

You can configure the AR637T receiver wirelessly, directly from any compatible Spektrum™ transmitter, through the Forward Programming menu. No separate computer or mobile device is needed for setup and adjustments.

 

SAFE® TECHNOLOGY

SAFE® (Sensor Assisted Flight Envelope) technology flight modes help pilots avoid over-controlling their models. SAFE uses AS3X to deliver normal flight performance, but with limited bank and pitch angles to prevent the aircraft from getting in extreme attitudes.

 

SAFE® PANIC RECOVERY

Sometimes called a bailout mode, Panic is a SAFE Stabilization mode that can return an airplane to level flight from any attitude. It is usually assigned to a momentary button.

 

SMART TELEMETRY

To enjoy the full benefits of Smart™ technology, use the AR637T receiver with a Smart ESC and telemetry capable Spektrum DSMX® transmitter. Vital telemetry data such as current, voltage, temperature and RPM is sent directly to your transmitter in real time. For more information on Smart Technology please visit our Spektrum Smart Technology page.

 

INTEGRATED BAROMETER

The Spektrum™ AR637T receiver features an integrated barometer (built-in pressure sensor) to provide altitude and vario telemetry data without the need to purchase additional sensor modules.

 

Specifications

Antenna Length
6.10" (155mm) and 7.32" (186mm)
Application
Airplane, Sailplane
Band
2.4GHz
Bind Method
Bind Button
Channels
6
Data Port
No
Failsafe
Yes
Flight Log Compatible
No
Forward Programming
Yes
Input Voltage
3.5 - 9V
Integrated Variometer
Yes
Modulation
DSMX
Product Application
Air, Sailplanes
Product Height
0.595" (15.02mm)
Product Length
1.96" (49.8mm)
Product Weight
0.42oz (12g)
Product Width
0.94" (23.3mm)
Programmable
Yes
Range
Full
Remote Receiver Ports
1
Resolution
2048
Rev Limiter
No
Serial Out
SRXL2
Technology 
SAFE / AS3X
Telemetry
Integrated
Telemetry Range
Full
Water-Resistant
No
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Par
Houston, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
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Richard Hackathorn
Port Orchard, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022
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Amazon Customer
New York, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025
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Kindle Customer
Lake Worth, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
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Tommy Jonsson
San Leandro, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026

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