# 187: Self-Driving Arm

- Show: [Embedded.fm](https://hardwarepodcasts.com/podcast/embedded-fm)
- Published: 2017-02-15
- Length: 1h 12m
- Page: https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm
- Listen: https://makingembeddedsystems.libsyn.com/187-self-driving-arm

## Summary

Patrick Pilarski, a Canada Research Chair at the University of Alberta, discusses his work on smart prosthetic limbs that use machine intelligence to bridge the gap between limited biological signals and complex robotic actuators. He explains how reinforcement learning allows prostheses to learn from trial and error in real-time, using techniques like 'prosthetic falconry' where a robotic limb learns by observing a user's healthy biological arm. Pilarski highlights the shift from simple myoelectric controls to systems that predict user intent and context, such as using cameras to identify objects like soup or doorknobs to pre-shape grips. He also outlines accessible tools for engineers, including Weka, OpenIA Gym, and Robotis Dynamixel servos, to get started with reinforcement learning robotics.

## Chapters

- [0:06](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=6) Introduction: Patrick Pilarski and Smart Prosthetics
- [3:31](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=211) The Challenge of Controlling Robotic Limbs with Limited Signals
- [8:05](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=485) Current State of the Art: Body-Powered vs. Myoelectric Prostheses
- [16:54](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=1014) Defining Machine Intelligence vs. Artificial Intelligence and Deep Learning
- [28:10](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=1690) Reinforcement Learning: Learning from Trial and Error in Real-Time
- [35:46](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=2146) Sensors, IoT, and Feedback Loops in Prosthetic Design
- [50:37](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=3037) User Preferences: Cosmesis, Function, and the Cybathlon Competition
- [1:03:46](https://hardwarepodcasts.com/podcast/embedded-fm/2017-02-15-187-self-driving-arm#t=3826) Getting Started with Reinforcement Learning: Weka, OpenIA Gym, and Robotis Servos

## Topics

- [Embedded firmware](https://hardwarepodcasts.com/topic/embedded-firmware)
- [Robotics & autonomy](https://hardwarepodcasts.com/topic/robotics-and-autonomy)
- [AI & machine learning](https://hardwarepodcasts.com/topic/ai-and-machine-learning)
- [Sensors & measurement in products](https://hardwarepodcasts.com/topic/sensors)
- [Medical & health devices](https://hardwarepodcasts.com/topic/medical-devices)
- [Industrial & consumer product design](https://hardwarepodcasts.com/topic/industrial-design)

## Most relevant to

early-stage companies

## Mentioned

- University of Alberta (company)
- Alberta Machine Intelligence Institute (company)
- Weka (tool)
- OpenIA Gym (tool)
- Robotis Dynamixel (chip)
- Myo (product)
- Thalmic Labs (company)
- Cybathlon (product)
- Co-AP (company)

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- [184. Bionics Help Amputees Take Big Strides Forward](https://hardwarepodcasts.com/podcast/the-next-byte-podcast/2024-07-23-184-bionics-help-amputees-take-big-strides-forward) (The Next Byte Podcast)
- [156. 2023 Recap & First Annual Saucies!🥫🍾](https://hardwarepodcasts.com/podcast/the-next-byte-podcast/2024-01-09-156-2023-recap-first-annual-saucies) (The Next Byte Podcast)
- [53. Mind-Control and Bug-Like Robots](https://hardwarepodcasts.com/podcast/the-next-byte-podcast/2022-01-18-53-mind-control-and-bug-like-robots) (The Next Byte Podcast)
- [229. Teaching Robots to Play Badminton](https://hardwarepodcasts.com/podcast/the-next-byte-podcast/2025-09-23-229-teaching-robots-to-play-badminton) (The Next Byte Podcast)

## Citing this page

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