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. 2019 Nov 20;4(4):74.
doi: 10.3390/biomimetics4040074.

A Case Study of Adding Proactivity in Indoor Social Robots Using Belief-Desire-Intention (BDI) Model

Ujjwal K C  1 , Jacques Chodorowski  2
Affiliations

A Case Study of Adding Proactivity in Indoor Social Robots Using Belief-Desire-Intention (BDI) Model

Ujjwal K C et al. Biomimetics (Basel). .

Abstract

The rise of robots and robotics has proved to be a benefaction to humankind in different aspects. Robotics evolved from a simple button, has seen massive development over the years. Consequently, it has become an integral part of human life as robots are used for a wide range of applications ranging from indoor uses to interplanetary missions. Recently, the use of social robots, in commercial indoor spaces to offer help or social interaction with people, has been quite popular. As such, taking the increasing use of social robots into consideration, many works have been carried out to develop the robots to make them capable of acting like humans. The notion behind this development is the need for robots to offer services without being asked. Social robots should think more like humans and suggest possible and suitable actions by analyzing the environment where they are. Belief-desire-intention (BDI) is one of the most popular models for developing rational agents based on how humans act based on the information derived from an environment. As such, this work defines a foundation architecture to integrate a BDI framework into a social robot to add "act like a human" feature for proactive behaviors. The work validates the proposed architecture by developing a vision-based proactive action using the PROFETA BDI framework in an indoor social robot, Waldo, operated by the robot operating system (ROS).

Keywords: belief–desire–intention (BDI) model; proactivity; robot operating system (ROS); social robots.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Waldo.
Figure 2
Figure 2
System overview.
Figure 3
Figure 3
CvBridge interface.
Figure 4
Figure 4
Interaction between different nodes in robot operating system (ROS) ecosystem.
Figure 5
Figure 5
Case: no person detected (a) BDI execution and (b) image feed collected by eyes of Waldo.
Figure 6
Figure 6
Case: person detected (a) BDI execution and (b) image feed collected by eyes of Waldo.
Figure 7
Figure 7
False negatives.
Figure 8
Figure 8
False positives.
Figure 9
Figure 9
Precision-recall curve.
See this image and copyright information in PMC

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