Papers by Lars-Erik Janlert
A method for Learning from Demonstration (LFD) is presented and evaluated on a simulated Robosoft... more A method for Learning from Demonstration (LFD) is presented and evaluated on a simulated Robosoft Kompai robot. The presented algo-rithm, called Predictive Sequence Learning (PSL), builds fuzzy rules de-scribing temporal relations between sensory-motor events recorded while a human operator is tele-operating the robot. The generated rule base can be used to control the robot and to predict expected sensor events in response to executed actions. The rule base can be trained under dif-ferent contexts, represented as fuzzy sets. In the present work, contexts are used to represent different behaviors. Several behaviors can in this way be stored in the same rule base and partly share information. The context that best matches present circumstances can be identified using the predictive model and the robot can in this way automatically identify the most suitable behavior for precent circumstances. The performance of PSL as a method for LFD is evaluated with, and without, contextual in-for...
Journal of Applied Logic, 2008
Programming normally proceeds from subjective method to objective method: to program a task, you ... more Programming normally proceeds from subjective method to objective method: to program a task, you need to be able to do the task; at least "in principle." Some new techniques of producing programs, exemplified by evolutionary algorithm techniques, do not involve any such subjective method. Is this still programming, and are the results really programs? To answer, the concept of program is reexamined. It is argued that in addition to being causative and descriptive, a program must also be rationally justifiable, i.e., the specific structure of the program should be explainable by the (rational) ways in which it contributes to achieving the intended goal. Whereas traditional programming is rational in the sense that it provides the program with a rationale by its reliance on subjective method and problem solving, these new techniques of "dark programming" do not produce any rationale; moreover, the results are not restricted to be easily rationalized. Dark programs are not guaranteed to be proper programs, but dark programming can still be used as a tool in proper (rational) programming. The business of programming then takes a turn from problem solving in the sense of invention and engineering towards problem solving in the sense of explanation and research.
Journal for the Theory of Social Behaviour, 1987
2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2013
This paper gives a brief overview of challenges in designing cognitive architectures for Learning... more This paper gives a brief overview of challenges in designing cognitive architectures for Learning from Demonstration. By investigating features and functionality of some related architectures, we propose a modular architecture particularly suited for sequential learning high-level representations of behaviors. We head towards designing and implementing goal based imitation learning that not only allows the robot to learn necessary conditions for executing particular behaviors, but also to understand the intents of the tutor and reproduce the same behaviors accordingly.
2010 IEEE International Conference on Robotics and Automation, 2010
Two methods for behavior recognition are presented and evaluated. Both methods are based on the d... more Two methods for behavior recognition are presented and evaluated. Both methods are based on the dynamic temporal difference algorithm Predictive Sequence Learning (PSL) which has previously been proposed as a learning algorithm for robot control. One strength of the proposed recognition methods is that the model PSL builds to recognize behaviors is identical to that used for control, implying that the controller (inverse model) and the recognition algorithm (forward model) can be implemented as two aspects of the same model. The two proposed methods, PSLE-Comparison and PSLH-Comparison, are evaluated in a Learning from Demonstration setting, where each algorithm should recognize a known skill in a demonstration performed via teleoperation. PSLH-Comparison produced the smallest recognition error. The results indicate that PSLH-Comparison could be a suitable algorithm for integration in a hierarchical control system consistent with recent models of human perception and motor control.
Communications in Computer and Information Science, 2011
A model-free learning algorithm called Predictive Sequence Learning (PSL) is presented and evalua... more A model-free learning algorithm called Predictive Sequence Learning (PSL) is presented and evaluated in a robot Learning from Demonstration (LFD) setting. PSL is inspired by several functional models of the brain. It constructs sequences of predictable sensory-motor patterns, without relying on predened higher-level concepts. The algorithm is demonstrated on a Khepera II robot in four dierent tasks. During training, PSL generates a hypothesis library from demonstrated data. The library is then used to control the robot by continually predicting the next action, based on the sequence of passed sensor and motor events. In this way, the robot reproduces the demonstrated behavior. PSL is able to successfully learn and repeat three elementary tasks, but is unable to repeat a fourth, composed behavior. The results indicate that PSL is suitable for learning problems up to a certain complexity, while higher level coordination is required for learning more complex behaviors.
Proceedings of the 28th international conference on Human factors in computing systems - CHI '10, 2010
The combination of virtual reality (VR) and brain measurements is a promising development of HCI,... more The combination of virtual reality (VR) and brain measurements is a promising development of HCI, but the maturation of this paradigm requires more knowledge about how brain activity is influenced by parameters of VR applications. To this end we investigate the influence of two prominent VR parameters, 3d-motion and interactivity, while brain activity is measured for a mental rotation task, using functional MRI (fMRI). A mental rotation network of brain areas is identified, matching previous results. The addition of interactivity increases the activation in core areas of this network, with more profound effects in frontal and preparatory motor areas. The increases from 3d-motion are restricted to primarily visual areas. We relate these effects to emerging theories of cognition and potential applications for brain-computer interfaces (BCIs). Our results demonstrate one way to provoke increased activity in task-relevant areas, making it easier to detect and use for adaptation and development of HCI.
Lecture Notes in Computer Science, 2007
Recognizing activities based on an actor's object manipulation is an important research approach ... more Recognizing activities based on an actor's object manipulation is an important research approach within ubiquitous computing. We present an approach which complements object manipulation with an actor's situational information by viewing the everyday objects used by the actor to perform his/her activities from an "egocentric perspective". Two concepts, namely observable space and manipulable space, are introduced as part of a situative space model inspired by the situated action theory to capture the changes in the set of objects seen and in the set of objects touchable by an actor in recognizing activities. A detailed evaluation of our prototype activity recognition system in virtual-reality environment is presented as a "proof of concept". We obtained a recognition precision of 89% on the activity-level and 76% on the action-level among 10 everyday home activities using our situative space model. Virtual reality was used as a test-bed in order to speed up the design process, compensate for the limitations with currently available sensing technologies and to compare the contributions of observable space, manipulable space and object manipulation.
Design Studies, 1997
People, as well as things, appear to have character--high-level attributes that help us understan... more People, as well as things, appear to have character--high-level attributes that help us understand and relate to them. A character is a coherent set of characteristics and attributes that apply to appearance and behaviour alike, cutting across different functions, situations and value systems--esthetical, technical, ethical--providing support for anticipation, interpretation and interaction. Consistency in character may become more important than ever in the increasingly complex artifacts of our computer-supported future. © 1997 Elsevier Science Ltd.
Abstract: In this paper we present an approach for high-level behavior recognition and selection ... more Abstract: In this paper we present an approach for high-level behavior recognition and selection integrated with a low-level controller to help the robot to learn new skills from demonstrations. By means of Semantic Network as the core of the method, the robot gains the ability to model the world with concepts and relate them to low-level sensory-motor states. We also show how the generalization ability of Semantic Networks can be used to extend learned skills to new situations.
The idea of realistic HCI, as described with Reality-Based Interaction, continuously adapting to ... more The idea of realistic HCI, as described with Reality-Based Interaction, continuously adapting to the users experience of the interaction, is a grand vision. Reality-Based Brain-Computer Interaction (RBBCI) is a conception of a system implementing this idea by combining Virtual Reality with functional brain imaging (fMRI) and appropriate methods of analysis and interpretation. The development of such systems can benefit greatly from a solid grounding in emerging theories of cognition and the brain. We present examples of such cognitive grounding and relate them to RBBCI, models of interaction and methods for interpretation of brain measurements. Recent results include the effect of interactivity on brain activity measurements in an immersive VR environment.
Proc. CHI 2009 Workshop on Challenges in the Evaluation of Usability and User Experience in Reality Based Interaction, 2009
We have developed a system where the combination of functional brain imaging (fMRI) and Virtual R... more We have developed a system where the combination of functional brain imaging (fMRI) and Virtual Reality (VR) can be used to study and evaluate user experience based on brain activation and models of cognitive neuroscience. The ability to study the brain during natural interaction with an (ecologically valid) environment has great potential for several areas of research and development, including evaluation of Reality-Based Interaction (RBI). The RBI concept of tradeoffs is of particular interest since we want to ...
Workshop on Designing Technology for People with Cognitive Impairments, CHI2006, Apr 1, 2006
This position paper outlines the easyADL project, a two-year project investigating the possibilit... more This position paper outlines the easyADL project, a two-year project investigating the possibility of using wearable technology to assist people suffering the dementia disease in performing Activities of Daily Living (ADL). An introduction to the egocentric interaction modeling framework is provided and the virtual reality based development methodology is discusssed.
ACM Transactions on Computer-Human Interaction, 2010
An almost explosive growth of complexity puts pressure on people in their everyday doings. Digita... more An almost explosive growth of complexity puts pressure on people in their everyday doings. Digital artifacts and systems are at the core of this development. How should we handle complexity aspects when designing new interactive devices and systems? In this article we begin an analysis of interaction complexity. We portray different views of complexity; we explore not only negative aspects of complexity, but also positive, making a case for the existence of benign complexity. We argue that complex interaction is not necessarily bad, but designers need a deeper understanding of interaction complexity and need to treat it in a more intentional and thoughtful way. We examine interaction complexity as it relates to different loci of complexity: internal, external, and mediated complexity. Our purpose with these analytical exercises is to pave the way for design that is informed by a more focused and precise understanding of interaction complexity.
Robotics and Autonomous Systems, 2015
Uploads
Papers by Lars-Erik Janlert