Tech Unbound Podcast EP5: Robot Able to Instantly Identify Household Materials Without Touching Objects

External News Details
Media
  • Tech Unbound Podcast with the GVU Center Tech Unbound Podcast with the GVU Center
    (image/png)

Georgia Tech researchers have developed a scalable and cost-effective way robots can identify materials of objects in the home without touching the objects. PhD robotics student Zackory Erickson, advised by Charlie Kemp, joins the Tech Unbound Podcast to share how it works.

Using near-infrared light, similar to what’s used in TV remotes, the robot can identify common materials used in household objects to better inform its actions. This might allow intelligent machines to understand, for example, the right bowl (paper versus metal) to put in a microwave or how hard to grasp a cup made of glass versus plastic.

Additional Information

Groups

College of Computing, GVU Center, School of Interactive Computing, ML@GT

Categories
No categories were selected.
Keywords
No keywords were submitted.
Status
  • Created By: Joshua Preston
  • Workflow Status: Published
  • Created On: Jun 27, 2019 - 8:41am
  • Last Updated: Jul 17, 2019 - 4:21pm