|
|
|
|
LEADER |
02856 am a22003013u 4500 |
001 |
119394 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Maurice, Pauline
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
|e contributor
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Mechanical Engineering
|e contributor
|
100 |
1 |
0 |
|a Huber, Meghan E
|e contributor
|
100 |
1 |
0 |
|a Hogan, Neville
|e contributor
|
100 |
1 |
0 |
|a Sternad, Dagmar
|e contributor
|
700 |
1 |
0 |
|a Huber, Meghan E
|e author
|
700 |
1 |
0 |
|a Hogan, Neville
|e author
|
700 |
1 |
0 |
|a Sternad, Dagmar
|e author
|
245 |
0 |
0 |
|a Velocity-Curvature Patterns Limit Human-Robot Physical Interaction
|
260 |
|
|
|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2018-12-03T17:45:20Z.
|
856 |
|
|
|z Get fulltext
|u http://hdl.handle.net/1721.1/119394
|
520 |
|
|
|a Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.
|
520 |
|
|
|a National Institutes of Health (U.S.) (NIH-R01-HD087089)
|
520 |
|
|
|a National Science Foundation (U.S.). National Robotics Initiative (NSF-NRI 1637854)
|
520 |
|
|
|a National Science Foundation (U.S.). National Robotics Initiative (NSF-NRI 1637824)
|
520 |
|
|
|a National Science Foundation (U.S.). EArly-concept Grants for Exploratory Research (NSF-EAGER 1548514)
|
520 |
|
|
|a National Science Foundation (U.S.). EArly-concept Grants for Exploratory Research (NSF-EAGER 1548501)
|
520 |
|
|
|a Eric P. and Evelyn E. Newman Fund
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t IEEE Robotics and Automation Letters
|