https://github.com/ctu-vras/pps-normative-model

A normative model of peripersonal space encoding as performing impact prediction.

https://github.com/ctu-vras/pps-normative-model

Science Score: 13.0%

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  • CITATION.cff file
  • codemeta.json file
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  • DOI references
    Found 4 DOI reference(s) in README
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    Low similarity (5.1%) to scientific vocabulary
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A normative model of peripersonal space encoding as performing impact prediction.

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Created over 4 years ago · Last pushed over 2 years ago
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README.md

pps-normative-model

This repository stores code related to the article A normative model of peripersonal space encoding as performing impact prediction. by Z. Straka, J.-P. Noel and M. Hoffmann link. The model is implemented in Matlab.

Citation: Straka Z, Noel J-P, Hoffmann M (2022) A normative model of peripersonal space encoding as performing impact prediction. PLoS Comput Biol 18(9): e1010464. https://doi.org/10.1371/journal.pcbi.1010464

calculate_PPS.m

Run this code to get a figure with dependency between the mean of 1000 predicted tactile activations (for each distance) and distance xT (in centimeters) of the stimuli from the body. Moreover, 25th and 75th percentils are plotted. Feel free to change the parameters of the experiment and compare the PPS profile with empirical data.

calculate_PPS3D.m

A 3D version of calculate_PPS.m.

PPSpredictionbayes.m

This function implements future position estimation which is followed by calculation of the Bayesian decision/prediction.

PPSpredictionbayes3D.m

A 3D version of PPSpredictionbayes.m.

FNstdPPS_properties.m

Plot S8 Fig (for one prediction time step size).

Owner

  • Name: Vision for Robotics and Autonomous Systems
  • Login: ctu-vras
  • Kind: organization
  • Location: Prague

Research group at Czech Technical University in Prague (CTU), Faculty of Electrical Engineering, Department of Cybernetics

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