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Social robot response to negative emotions as a PDDL planning problem in the presence of uncertainty

Probierz Eryka, Gałuszka Anita, Gałuszka Adam

Przegląd Elektrotechniczny

2023

R. 99, nr 8

33--37

We propose to use automatic scheduling in the presence of uncertainty methodology to analyze the emotional state of a person and possible responses of a social robot. The emotions considered were: Sadness, Fear, Anger, Disgust and Contempt. The scenarios considered include modelling uncertainty in emotion detection. The result of the work is a set of two planning domains with illustrative examples. It was assumed that when negative emotions are detected, the robot should react in such a way as to reduce or not escalate them.

Proponujemy wykorzystanie metodologii automatycznego planowania w obecności niepewności do analizy stanu emocjonalnego osoby i możliwych reakcji robota społecznego. Rozważane emocje to: Smutek, Strach, Złość, Obrzydzenie i Pogarda. Rozważane scenariusze obejmują modelowanie niepewności w detekcji emocji. Efektem pracy jest zestaw dwóch domen planistycznych wraz z ilustrującymi je przykładami. Założono, że w przypadku wykrycia negatywnych emocji robot powinien reagować w taki sposób, aby je zmniejszyć lub nie eskalować.

The methods of performing the viewshed analyses on inland waters for complex objects

Łubczonek J.

Zeszyty Naukowe / Akademia Morska w Szczecinie

2013

nr 35 (107)

97--102

Observational sensors, such as CCTV cameras and radars, are part of the RIS system. These sensors should provide information about the current situation on the waterway and to a greater extent – aquatory. Barriers for the observational sensor, in the sense of reducing the view field, are various objects in the aquatory. This is one of the main factors that make it difficult to determine the proper location of the sensor. Currently, in order to increase the efficiency of determining the locations of the observational sensors are used different tools for performing spatial analysis. This applies to both the initial geographical identification as well as detailed analysis. Analysis efficiency, in turn, depends on the model of the environment, represented in the form of the Digital Surface Model. Given the complexity of some geographic features, it should be used the appropriate methodology for the visibility analysis, as well as the preparation of the input material. The following work includes the theme of visibility analysis on inland waters, with special emphasis on the complex objects. They include bridges, cranes, buildings, high vegetation and other engineering structures.