| Record Number | 10262 |
| Reference Type | Conference Proceedings |
| Author(s) | Hoffmann, H.;Pastor, P.;Park, D.-H.;Schaal, S. |
| Year | 2009 |
| Title | Biologically-inspired dynamical systems for movement generation: automatic real-time goal adaptation and obstacle avoidance |
| Journal/Conference/Book Title | International Conference on Robotics and Automation (ICRA2009) |
| Keywords | movement primitives, dynamic systems, obstacle avoidance, generalization |
Abstract |
We introduce a framework for generating robotic
movements. Movements can be learned from human demonstration
and generalized to new contexts. We use a dynamical
system to represent a movement unit. The advantage of the
dynamical-system description is that the attractor dynamics
automatically correct for perturbations. To reproduce a
desired movement, we can shape a non-linear differential
equation, which generates the movement. This article presents
an improved modification of the original dynamic movement
primitive (DMP) framework by Ijspeert et al [1], [2]. The new
equations can generalize movements to new targets without
singularities and large accelerations. Furthermore, the new
equations can represent a movement in 3D task space without
depending on the choice of coordinate system. Our modified
DMP is motivated from convergent force fields in frog. We
further extend the formalism to obstacle avoidance by exploiting
the robustness against perturbations. An additional term is
added to the differential equations to make the robot steer
around an obstacle. This additional term empirically describes
human obstacle avoidance. We demonstrate the feasibility of
our approach using the Sarcos Slave robot arm: after learning
a single placing movement, the robot placed a cup between two
arbitrarily given positions and avoided approaching obstacles.
|
| Notes | clmc |
| URL(s) | http://www-clmc.usc.edu/publications/H/hoffmann-ICRA2009.pdf
|
| Link to PDF | http://www-clmc.usc.edu/publications//H/hoffmann-ICRA2009.pdf |
| Place Published | Kobe, Japan, May 12-19, 2009 |
| Short Title | Biologically-inspired dynamical systems for movement generation: automatic real-time goal adaptation and obstacle avoidance |
