Intelligent Trustworthy Robotic Unit Supporting Transport and User needs
Problem statement
Imagine working in a warehouse carrying boxes and other large items with robots on the last leg of your eight hour shift, your fatigue has reached its limit and your body is on its last legs. The robot, however, is unfazed and continues at the same pace with no regard to you in mind, leading to damaged merchandise or worse, injured workers. This example is not far from reality with companies like Amazon starting to implement humanoid robots in their factories [1]. Quantifying and observing this fatigue in human robot interaction will be crucial to understanding how to make robots respond more dynamically in these situations, allowing robots to be more of a tool than a replacement. This is what our client, Professor Ranjana Mehta and Aakash Yadav from the NeuroErgonomics lab, hopes to help quantify and solve. A few studies in the past such as “An Integrated Framework for Human–Robot Collaborative Manipulation” [2] and “An Integrated Framework for Human–Robot Collaborative Manipulation” [3], have investigated this human robot lifting interaction, however, they use less than three sensors [2] and never delve into the issue of repetition and fatigue [3]. Professor Ranjana Mehta and Aakash Yadav plan on obtaining a complete scope of this problem, using more than five sensors and studies that last for more than seven hours. The integration of data streaming and collection of these sensors is a complex task; all of them are highly independent from one another. The experimental objects also require utmost comfortability and adjustability, since participants from all different backgrounds will use them for more than seven hours. As a team, we hope to deliver a cohesive testing platform for fatigue, with a well integrated data streaming and collection system combining these multitude of sensors. We also hope to deliver a testing platform with comfortability and adjustment in mind, while making sure it is optimal for the study’s purposes. Ultimately, we believe that our platform will provide a way for the NeuroErgonomics lab to conduct high quality research on the effects of fatigue, developing the framework for human robot interaction of the future. [1] Law, M. (2023, October 20). Amazon trials humanoid warehouse robots to support workforce. Technology Magazine. https://technologymagazine.com/articles/amazon-trials-humanoid-warehouse-robots-to-support-workforce [2] Sheng, Weihua & Thobbi, Anand & Gu, Ye. (2014). An Integrated Framework for Human–Robot Collaborative Manipulation. IEEE transactions on cybernetics. 45. 10.1109/TCYB.2014.2363664. [3] Mielke E, Townsend E, Wingate D, Salmon JL, Killpack MD. Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads. Front Neurorobot. 2024 Feb 12;18:1291694. Doi: 10.3389/fnbot.2024.1291694. PMID: 38410142; PMCID: PMC10894988.
Team members
Nick Kelly – facilitator
Eric Ouyang – communicator
Logan Danks – accountant
Ryan Mikol – admin
Client
Ranjana Mehta
ISyE NeuroErgonomics Lab