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Generation of human walking paths

Papadopoulos, Alessandro Vittorio LU ; Bascetta, Luca and Ferretti, Gianni (2016) In Autonomous Robots 40(1). p.59-75
Abstract
This work investigates the way humans plan their paths in a goal-directed motion, assuming that a person acts as an optimal controller that plans the path minimizing a certain (unknown) cost function. Taking this viewpoint, the problem can be formulated as an inverse optimal control one, i.e., starting from control and state trajectories one wants to figure out the cost function used by a person while planning the path. The so-obtained model can be used to support the design of safe human-robot interaction systems, as well as to plan human-like paths for humanoid robots. To test the envisaged ideas, a set of walking paths of different volunteers were recorded using a motion capture facility. The collected data were used to compare two... (More)
This work investigates the way humans plan their paths in a goal-directed motion, assuming that a person acts as an optimal controller that plans the path minimizing a certain (unknown) cost function. Taking this viewpoint, the problem can be formulated as an inverse optimal control one, i.e., starting from control and state trajectories one wants to figure out the cost function used by a person while planning the path. The so-obtained model can be used to support the design of safe human-robot interaction systems, as well as to plan human-like paths for humanoid robots. To test the envisaged ideas, a set of walking paths of different volunteers were recorded using a motion capture facility. The collected data were used to compare two solutions to the inverse optimal control problem coming from the literature to a novel one. The obtained results, ranked using the discrete Fréchet distance, show the effectiveness of the proposed approach. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Optimal control, Human-like path planning, Human-centered design, Humanoid robots, Safe human-robot interaction
in
Autonomous Robots
volume
40
issue
1
pages
59 - 75
publisher
Springer
external identifiers
  • wos:000368802400004
  • scopus:84953370935
ISSN
0929-5593
DOI
10.1007/s10514-015-9443-2
project
LCCC
language
English
LU publication?
yes
id
5ca8330f-2226-449f-9ede-8abace1f9fa9 (old id 7374018)
date added to LUP
2015-06-29 11:11:45
date last changed
2017-02-05 04:08:36
@article{5ca8330f-2226-449f-9ede-8abace1f9fa9,
  abstract     = {This work investigates the way humans plan their paths in a goal-directed motion, assuming that a person acts as an optimal controller that plans the path minimizing a certain (unknown) cost function. Taking this viewpoint, the problem can be formulated as an inverse optimal control one, i.e., starting from control and state trajectories one wants to figure out the cost function used by a person while planning the path. The so-obtained model can be used to support the design of safe human-robot interaction systems, as well as to plan human-like paths for humanoid robots. To test the envisaged ideas, a set of walking paths of different volunteers were recorded using a motion capture facility. The collected data were used to compare two solutions to the inverse optimal control problem coming from the literature to a novel one. The obtained results, ranked using the discrete Fréchet distance, show the effectiveness of the proposed approach.},
  author       = {Papadopoulos, Alessandro Vittorio and Bascetta, Luca and Ferretti, Gianni},
  issn         = {0929-5593},
  keyword      = {Optimal control,Human-like path planning,Human-centered design,Humanoid robots,Safe human-robot interaction},
  language     = {eng},
  number       = {1},
  pages        = {59--75},
  publisher    = {Springer},
  series       = {Autonomous Robots},
  title        = {Generation of human walking paths},
  url          = {http://dx.doi.org/10.1007/s10514-015-9443-2},
  volume       = {40},
  year         = {2016},
}