There are many arenas where humans outperform machines. For example, when coordinated interaction with the physical environment is needed, humans (and animals) vastly out-perform modern robots. This occurs despite the biological systems having far slower 'hardware' and 'wetware' and much greater complexity than even the most modern robots. This research project seeks to understand the role of complexity in human sensory and motor performance. Human walking under challenging balance conditions will be studied and the use of canes to enhance stability will be included. The investigators emphasis on learning to balance in challenging environments should lead to new rehabilitation therapies (with or without robotic assistance) to aid recovery of balance and walking (e.g., after stroke). The researchers will create educational units suitable for online presentation to K-12 students and will devise exhibits based on their research for the Museum of Science in Boston.

The central hypothesis to be tested in this project is that complex movements involving physical interaction with objects are organized as a hierarchy formed of modules or primitives. Experiments will study how unimpaired humans learn to walk on narrow beams. Beams of different roundness will vary the challenge. Hand-held canes will alter the available support (like training wheels on a child's bicycle). Computer simulations combined with machine learning will study the benefits and drawbacks of organization as a hierarchy. New mathematical tools will be developed and tested to see if they enable insightful description of human performance in challenging conditions. The research involves a multinational collaboration among scientists from the U.S., Israel, and Germany, each with complementary expertise. The bridge between experimental and theoretical work and the diverse Principal Investigators will help to attract women into the traditionally male-dominated fields of computational neuroscience, robotics and control engineering. Companion projects are being funded by the Federal Ministry of Education and Research, Germany (BMBF) and the US-Israel Binational Science Foundation (BSF).

Project Start
Project End
Budget Start
2017-09-01
Budget End
2021-10-31
Support Year
Fiscal Year
2017
Total Cost
$300,000
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139