Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Emotionally Intelligent Robot: Improving Social Navigation in
  Crowded Environments   We present a real-time algorithm for emotion-aware navigation of a robot
among pedestrians. Our approach estimates time-varying emotional behaviors of
pedestrians from their faces and trajectories using a combination of
Bayesian-inference, CNN-based learning, and the PAD
(Pleasure-Arousal-Dominance) model from psychology. These PAD characteristics
are used for long-term path prediction and generating proxemic constraints for
each pedestrian. We use a multi-channel model to classify pedestrian
characteristics into four emotion categories (happy, sad, angry, neutral). In
our validation results, we observe an emotion detection accuracy of 85.33%. We
formulate emotion-based proxemic constraints to perform socially-aware robot
navigation in low- to medium-density environments. We demonstrate the benefits
of our algorithm in simulated environments with tens of pedestrians as well as
in a real-world setting with Pepper, a social humanoid robot.

5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci