Uploaded November 2024 | Updated September 2026, 2 weeks ago
#tipartner
At Electronica 2024, Electomaker took a look at the latest advancements in robotics presented by Texas Instruments (TI). Among these innovations is an exciting demonstration of human pose estimation technology, merging AI and real-time processing to empower robotic arms with remarkable precision.
This robotic pick-and-place is powered by the phyCORE-AM68A system-on-module (SOM) and utilizes the AM68A Arm®-based processor which features a deep learning accelerator with an edge AI-based human pose estimation model. Visual data is pipelined through the AM68A SoC acceleration units in order to analyze the key points of the human pose annotation which is then used to control the position of the robotic arm.
For more information, please visit: ti.com/applications/industrial/robotics/overview.html
▬ Contents of this video ▬▬▬▬▬▬▬▬▬▬
0:00 - Introduction to Pose Estimation and Robotics
0:21 - Overview of Energy-Efficient AI for Robotics
0:40 - Demonstration of Pose Estimation with Robotic Arm
1:13 - Challenges of Pose Estimation in Busy Environments
1:36 - Hands-On Robot Control with Pose Estimation
1:53 - Advantages of Pose Estimation in Robotics
2:08 - Use Cases for Hazardous Environments
2:36 - Teaching Robots Through Instinctive Movements
2:45 - AM68 Processor and Hardware Acceleration
▬ Show references and links ▬▬▬▬▬▬▬▬▬▬
ti.com/applications/industrial/robotics/overview.html
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#tipartner
At Electronica 2024, Electomaker took a look at the latest advancements in robotics presented by Texas Instruments (TI). Among these innovations is an exciting demonstration of human pose estimation technology, merging AI and real-time processing to empower robotic arms with remarkable precision.
This robotic pick-and-place is powered by the phyCORE-AM68A system-on-module (SOM) and utilizes the AM68A Arm®-based processor which features a deep learning accelerator with an edge AI-based human pose estimation model. Visual data is pipelined through the AM68A SoC acceleration units in order to analyze the key points of the human pose annotation which is then used to control the position of the robotic arm.
For more information, please visit: ti.com/applications/industrial/robotics/overview.html
▬ Contents of this video ▬▬▬▬▬▬▬▬▬▬
0:00 - Introduction to Pose Estimation and Robotics
0:21 - Overview of Energy-Efficient AI for Robotics
0:40 - Demonstration of Pose Estimation with Robotic Arm
1:13 - Challenges of Pose Estimation in Busy Environments
1:36 - Hands-On Robot Control with Pose Estimation
1:53 - Advantages of Pose Estimation in Robotics
2:08 - Use Cases for Hazardous Environments
2:36 - Teaching Robots Through Instinctive Movements
2:45 - AM68 Processor and Hardware Acceleration
▬ Show references and links ▬▬▬▬▬▬▬▬▬▬
ti.com/applications/industrial/robotics/overview.html
▬ Support us! ▬▬▬▬▬▬▬▬▬▬
We publish a new show every week. Subscribe here: youtube.com/channel/UCiMO2NHYWNiVTzyGsPYn4DA?sub_confirmation=1
We stock the latest products from Adafruit, Seeed Studio, Pimoroni, Sparkfun, and many more! Browse our shop:
electromaker.io/shop
Join us on Discord! discord.com/invite/w8d7mkCkxj
Follow us on Twitter: twitter.com/ElectromakerIO
Like us on Facebook: facebook.com/electromaker.io
Follow us on TikTok: tiktok.com/@electromaker.io
Follow us on Instagram: instagram.com/electromaker_io
Don't have time to watch the show? Listen to the Electromaker Show in podcast format on your favourite podcast platform! directory.libsyn.com/shows/view/id/electromaker
