Sciweavers

Share
CAPTECH
1998
Springer

Artificial Neural Networks for Motion Emulation in Virtual Environments

8 years 11 months ago
Artificial Neural Networks for Motion Emulation in Virtual Environments
Simulation of natural human movement has proven to be a challenging problem, difficult to be solved by more or less traditional bioinspired strategies. In opposition to several existing solutions, mainly based upon deterministic algorithms, a data-driven approach is presented herewith, which is able to grasp not only the natural essence of human movements, but also their intrinsic variability, the latter being a necessary feature for many ergonomic applications. For these purposes a recurrent Artificial Neural Network with some novel features (recurrent RPROP, state neurons, weighted cost function) has been adopted and combined with an original pre-processing step on experimental data, resulting in a new hybrid approach for data aggregation. Encouraging results on human hand reaching movements are also presented.
Y. Bellan, Mario Costa, Giancarlo Ferrigno, Fabriz
Added 05 Aug 2010
Updated 05 Aug 2010
Type Conference
Year 1998
Where CAPTECH
Authors Y. Bellan, Mario Costa, Giancarlo Ferrigno, Fabrizio Lombardi, Luca Macchiarulo, Alfonso Montuori, Eros Pasero, Camilla Rigotti
Comments (0)
books