Expressive Motion Synthesis for Robot Actors in Robot Theatre

Lately, personal and entertainment robotics are becoming more and more common. In this thesis, the application of entertainment robots in the context of a Robot Theatre is studied. Specifically, the thesis focuses on the synthesis of expressive movements or animations for the robot performers (Robot Actors). The novel paradigm emerged from computer animation is to represent the motion data as a set of signals. Thus, preprogrammed motion data can be quickly modified using common signal processing techniques such as multiresolution filtering and spectral analysis. However, manual adjustments of the filtering and spectral methods parameters, and good artistic skills are still required to obtain the desired expressions in the resulting animation. Music contains timing, timbre and rhythm information which humans can translate into affect, and express the affect through movement dynamics, such as in dancing. Music data is then assumed to contain affective information which can be expressed in the movements of a robot. In this thesis, music data is used as input signal to generate motion data (Dance) and to modify a sequence of pre-programmed motion data (Scenario) for a custom-made Lynxmotion robot and a KHR-1 robot, respectively. The music data in MIDI format is parsed for timing and melodic information, which are then mapped to joint angle values. Surveys were done to validate the usefulness and contribution of music signals to add expressiveness to the movements of a robot for the Robot Theatre application

Evaluation of Laban Effort Features based on the Social Attributes and Personality of Domestic Service Robots

Today, it is not uncommon to see robots adopted in various domains and environments. From manufacturing facilities to households, robots take over several roles and tasks. For instance, the adoption of robotic vacuum cleaners has drastically increased in the recent decades. During their interaction with these embodied autonomous agents, humans tend to ascribe certain personality traits to them, even when the robot has a mechanoid appearance and very low degree-of-freedom. As the social capabilities and the persuasiveness of robots increase, design of robots with certain personality traits will become a significant design problem. The current advancements in AI and robotics will led to development of more realistic and persuasive robots in the foreseeable future. For this, it is crucial to understand people’s judgment of the robots’ social attributes since the findings can shape the future of personality and behavior design for social robots. Therefore, using only a simple and mono-functional robotic vacuum cleaner, this study aims to investigate the impact of expressive motions on how people perceive the social attributes and personality of the robot. To investigate this, the framework of Laban Effort Features was modified to fit the needs and constraints of a robotic vacuum cleaner. Expressive motions were designed for a simple cleaning task performed by iRobot’s Create2. The four movement features that have been controlled for robot include path planning behavior, radius of curvature at rotational turns, velocity, and vacuum power. Next, participants were asked to rate the personality and social attributes of the robot under several treatment conditions using a video-based online survey. Participants were recruited through the crowd-sourcing platform, Amazon Mechanical Turk. The results indicated that people’s ratings of personality and social attributes of the robot were influenced by the robot’s movement features. For social attributes, there were two main findings. First, velocity influenced robot’s ratings of warmth and competence. Second, path planning behavior influenced robot’s ratings of competence and discomfort. In terms of robot personality, the results indicated three main findings. First, random path planning behavior was associated with higher Neuroticism ratings. Second, high velocity yielded higher Agreeableness ratings. Third, vacuum power with higher duty cycle yielded higher Agreeableness and Conscientiousness ratings. In conclusion, this study showed the framework of Laban Effort Features can be applied to fit the cleaning task of a domestic service robot, and that the framework’s application makes a difference in how humans perceive the personality and social attributes of the robot. Overall, the findings should be considered in human-robot interaction when incorporating expressive motions and affective behavior into domestic service robots

Interactive dance choreography assistance

Creative support for the performing arts is prevalent in many fields, however, for the art of dance, automated tools supporting creativity have been scarce. In this research, we describe ongoing research into (semi)automatic automated creative choreography support. Based on state-of-the-art and a survey among 54 choreographers we establish functionalities and requirements for a choreography assistance tool, including the semantic levels at which it should operate and communicate with the end-users. We describe a user study with a prototype tool which presents choreography alternatives using various simple strategies in three dance styles. The results show that the needs for such a tool vary based on the dance discipline. In a second user study, we investigate various methods of presenting choreography variations. Here, we evaluate four presentation methods: textual descriptions, 2D animations, 3D animations and auditory instructions in two different dance styles. The outcome of the expert survey shows that the tool is effective in communicating the variations to the experts and that they express a preference for 3D animations. Based on these results, we propose a design for an interactive dance choreography assistant tool

Abstract expressions of affect

What form should happiness take? And how is disgust shaped? This research investigates how synthetic affective expressions can be designed with minimal reference to the human body. The authors propose that the recognition and attribution of affect expression can be triggered by appropriately presenting the bare essentials used in the mental processes that mediate the recognition and attribution of affect. The novelty of the proposed approach lies in the fact that it is based on mental processes involved in the recognition of affect, independent of the configuration of the human body and face. The approach is grounded in (a) research on the role of abstraction in perception, (b) the elementary processes and features relevant to visual emotion recognition and emotion attribution, and (c) how such features can be used (and combined) to generate a synthetic emotion expression. To further develop the argument for this approach they present a pilot study that shows the feasibility of combining affective features independently of the human configuration by using abstraction to create consistent emotional attributions. Finally, the authors discuss the potential implications of their approach for the design of affective robots. The developed design approach promises a maximization of freedom to integrate intuitively understandable affective expressions with other morphological design factors a technology may require, providing synthetic affective expressions that suit the inherently artificial and applied nature of affective technology