| 1. |
- Aktius, Malin, et al.
(författare)
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A Behavior-Based Model of the Hydra, Phylum Cnidaria
- 2007
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Ingår i: 9th European Conference, ECAL 2007. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540749127 ; , s. 1024-1033
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Konferensbidrag (refereegranskat)abstract
- Behavior-based artificial systems, e.g. mobile robots, are frequently designed using (various degrees and levels of) biology as inspiration, but rarely modeled based on actual quantitative empirical data. This paper presents a data-driven behavior-based model of a simple biological organism, the hydra. Four constituent behaviors were implemented in a simulated animal, and the overall behavior organization was accomplished using a colony-style architecture (CSA). The results indicate that the CSA, using a priority-based behavioral hierarchy suggested in the literature, can be used to model behavioral properties like latency, activation threshold, habituation, and duration of the individual behaviors of the hydra. Limitations of this behavior-based approach are also discussed.
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| 2. |
- Aktius, Malin, et al.
(författare)
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Kognitiv robotik
- 2012. - 1
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Ingår i: Kognitionsvetenskap. - : Studentlitteratur. - 9789144051666 ; , s. 551-560
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Bokkapitel (refereegranskat)
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| 3. |
- Alenljung, Beatrice, et al.
(författare)
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User Experience in Social Human-Robot Interaction
- 2017
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Ingår i: International Journal of Ambient Computing and Intelligence (IJACI). - : I G I Global. - 1941-6237 .- 1941-6245. ; 8:2, s. 12-31
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Tidskriftsartikel (refereegranskat)abstract
- Socially interactive robots are expected to have an increasing importance in human society. For social robots to provide long-term added value to people’s lives, it is of major importance to stressthe need for positive user experience (UX) of such robots. The human-centered view emphasizes various aspects that emerge in the interaction between humans and robots. However, a positive UX does not appear by itself but has to be designed for and evaluated systematically. In this paper, the focus is on the role and relevance of UX in human-robot interaction (HRI) and four trends concerning the role and relevance of UX related to socially interactive robots are identified, and three challenges related to its evaluation are also presented. It is argued that current research efforts and directions are not sufficient in HRI research, and that future research needs to further address interdisciplinary research in order to achieve long-term success of socially interactive robots.
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| 4. |
- Andler, Sten F., et al.
(författare)
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Information Fusion from Databases, Sensors and Simulations : A Collaborative Research Program
- 2005
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Ingår i: Proceedings. - : IEEE Computer Society. - 0769523064 ; , s. 234-241
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Konferensbidrag (refereegranskat)abstract
- This paper provides an overview of a collaborative research program in information fusion from databases, sensors and simulations. Information fusion entails the combination of data from multiple sources, to generate information that cannot be derived from the individual sources. This area is of strategic importance for industry and defense, as well as public administration areas such as health care, and needs to be pursued as an academic subject. A large number of industrial partners are supporting and participating in the development of the area. The paper describes the program’s general approach and main research areas, with a particular focus on the role of information fusion in systems development
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| 5. |
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| 6. |
- Billing, Erik, 1981-
(författare)
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Cognition reversed : Robot learning from demonstration
- 2009
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The work presented in this thesis investigates techniques for learning from demonstration (LFD). LFD is a well established approach to robot learning, where a teacher demonstrates a behavior to a robot pupil. This thesis focuses on LFD where a human teacher demonstrates a behavior by controlling the robot via teleoperation. The robot should after demonstration be able to execute the demonstrated behavior under varying conditions. Several views on representation, recognition and learning of robot behavior are presented and discussed from a cognitive and computational perspective. LFD-related concepts such as behavior, goal, demonstration, and repetition are defined and analyzed, with focus on how bias is introduced by the use of behavior primitives. This analysis results in a formalism where LFD is described as transitions between information spaces. Assuming that the behavior recognition problem is partly solved, ways to deal with remaining ambiguities in the interpretation of a demonstration are proposed. A total of five algorithms for behavior recognition are proposed and evaluated, including the dynamic temporal difference algorithm Predictive Sequence Learning (PSL). PSL is model-free in the sense that it makes few assumptions of what is to be learned. One strength of PSL is that it can be used for both robot control and recognition of behavior. While many methods for behavior recognition are concerned with identifying invariants within a set of demonstrations, PSL takes a different approach by using purely predictive measures. This may be one way to reduce the need for bias in learning. PSL is, in its current form, subjected to combinatorial explosion as the input space grows, which makes it necessary to introduce some higher level coordination for learning of complex behaviors in real-world robots. The thesis also gives a broad introduction to computational models of the human brain, where a tight coupling between perception and action plays a central role. With the focus on generation of bias, typical features of existing attempts to explain humans' and other animals' ability to learn are presented and analyzed, from both a neurological and an information theoretic perspective. Based on this analysis, four requirements for implementing general learning ability in robots are proposed. These requirements provide guidance to how a coordinating structure around PSL and similar algorithms should be implemented in a model-free way.
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| 7. |
- Billing, Erik, 1981-, et al.
(författare)
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Finding Your Way from the Bed to the Kitchen: Reenacting and Recombining Sensorimotor Episodes Learned from Human Demonstration
- 2016
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Ingår i: Frontiers in Robotics and Ai. - Lausanne, Switzerland : Frontiers Media SA. - 2296-9144. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- Several simulation theories have been proposed as an explanation for how humans and other agents internalize an "inner world" that allows them to simulate interactions with the external real world - prospectively and retrospectively. Such internal simulation of interaction with the environment has been argued to be a key mechanism behind mentalizing and planning. In the present work, we study internal simulations in a robot acting in a simulated human environment. A model of sensory-motor interactions with the environment is generated from human demonstrations and tested on a Robosoft Kompai robot. The model is used as a controller for the robot, reproducing the demonstrated behavior. Information from several different demonstrations is mixed, allowing the robot to produce novel paths through the environment, toward a goal specified by top-down contextual information. The robot model is also used in a covert mode, where the execution of actions is inhibited and perceptions are generated by a forward model. As a result, the robot generates an internal simulation of the sensory-motor interactions with the environment. Similar to the overt mode, the model is able to reproduce the demonstrated behavior as internal simulations. When experiences from several demonstrations are combined with a top-down goal signal, the system produces internal simulations of novel paths through the environment. These results can be understood as the robot imagining an "inner world" generated from previous experience, allowing it to try out different possible futures without executing actions overtly. We found that the success rate in terms of reaching the specified goal was higher during internal simulation, compared to overt action. These results are linked to a reduction in prediction errors generated during covert action. Despite the fact that the model is quite successful in terms of generating covert behavior toward specified goals, internal simulations display different temporal distributions compared to their overt counterparts. Links to human cognition and specifically mental imagery are discussed.
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| 8. |
- Billing, Erik, 1981-, et al.
(författare)
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Robot-Enhanced Therapy for Children with Autism
- 2018
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Ingår i: Proceedings of the 14th SweCog Conference. - Skövde : University of Skövde. - 9789198366730 ; , s. 19-22
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Konferensbidrag (refereegranskat)
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| 9. |
- Billing, Erik, PhD, 1981-, et al.
(författare)
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The DREAM Dataset : Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy
- 2020
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 15:8
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Tidskriftsartikel (refereegranskat)abstract
- We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general.
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| 10. |
- Biro, Zoltan, et al.
(författare)
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Evolution of visually-guided approach behaviour in recurrent artificial neural network robot controllers
- 1998
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Analysis of internal structures of embodied and situated agents may provide insights into the mechanisms underlying adaptive behaviour. This paper is concerned with the evolution and analysis of visually-guided approach behaviour in a simulated robotic agent controlled by a recurrent artificial neural network, whose connection weights have been evolved using evolutionary algorithms. Analysis of the evolved behaviours and their network-internal mechanisms reveals a behavioural structure and organization resembling a Brooksian subsumption architecture. The task decomposition, as well as the resulting individual behaviours and their integration, however, are realized as network-internal state space dynamics, evolved in the course of agent-environment interaction, i.e. with a minimum of designer intervention.
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