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Low-gravity environments in space pose a multitude of challenges to astronauts. Even seemingly simple motor skills such as grasping, locomotion, or lifting an object can become particularly challenging in such environments. At the same time, it is critical to exercise in space in order to avoid bone and muscle loss. In this project, we are investigating symbiotic human-robot interaction in order to assist astronauts in their activities while also maintaining healthy body function. In particular we are developing Space HeSA (Hip Exoskeleton for Superior Assistance), a lightweight assistive, robotic device for space exploration. Space HeSA uses state-of-the-art machine learning methods in order to interpret human intentions and proactively engage in current tasks.
We have developed a first prototype of the Space HeSA and have since improved it by creating a second iteration. In particular, we have designed an exoskeleton that can be worn through a belt and which assists humans in a variety of tasks, including walking and object lifting. In our latest iteration of the design, we reduced the overall weight of the HeSA and implemented machine learning algorithms that can predict and classify human motion. To this end, we have developed an Open Source library for Interaction Primitives - a machine learning methodology for representing and reasoning over human movements. Furthermore, we have developed new, compact PCB boards that can run the above algorithms in real-time while also minimizing power consumption.
New robotics technology developed within this project of the Interplanetary Initiative is also used to improve quality of work and life on earth.
The images show both the simulated version as well as the real exoskeleton.
Heni Ben AmorAssistant Professor, School of Computing Informatics, and Decision Systems Engineering, ASU
Sangram RedkarPolytechnic School, ASU
Thomas Sugar Polytechnic School, ASU
Simon StepputtisSchool of Computing Informatics, and Decision Systems Engineering, ASU
Xunguang LiPolytechnic School, ASU