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Integrating user interface agents with conventional applications

KNOWLEDGE-BASED SYSTEMS 1998年第1期11卷 15-23页

作者： Lieberman, H MIT Media Lab Cambridge MA 02139 USA

In most experiments with user interface agents to date, it has been necessary either to implement both the agent and the application from scratch, or to modify the code of an existing application to enable the necessary communication. Instead, we would like to be able to 'attach' an agent to an existing application, while requiring only a minimum of advance planning on the part of the application developer. Commercial applications an increasingly supporting the use of 'application programmers' interfaces' and scripting languages as means of achieving external control of applications. Are these mechanisms sufficient for software agents to achieve communication with applications? This paper reports some preliminary experiments in developing agent software that works with existing, unmodified commercial applications and agents that work across multiple applications. We describe a programming by example agent, ScriptAgent, that uses a scripting language, Applescript, to record example procedures that are generalized by the agent. Another approach is examinability, where the application grants to the agent the right to examine internal data structures. We present another kind of learning agent, Tatlin, that compares successive application states to infer interface operations. Finally, we discuss broader systems issues such as parallelism, interface sharing between agent and application, and access to objects. (C) 1998 Published by Elsevier Science B.V. All rights reserved.

关键词： agents scripting languages programming by example programming by demonstration machine learning user interface

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Socially guided intrinsic motivation for robot learning of motor skills

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AUTONOMOUS ROBOTS 2014年第3期36卷 273-294页

作者： Sao Mai Nguyen Oudeyer, Pierre-Yves INRIA Flowers Team Paris France ENSTA ParisTech Paris France

This paper presents a technical approach to robot learning of motor skills which combines active intrinsically motivated learning with imitation learning. Our algorithmic architecture, called SGIM-D, allows efficient learning of high-dimensional continuous sensorimotor inverse models in robots, and in particular learns distributions of parameterised motor policies that solve a corresponding distribution of parameterised goals/tasks. This is made possible by the technical integration of imitation learning techniques within an algorithm for learning inverse models that relies on active goal babbling. After reviewing social learning and intrinsic motivation approaches to action learning, we describe the general framework of our algorithm, before detailing its architecture. In an experiment where a robot arm has to learn to use a flexible fishing line, we illustrate that SGIM-D efficiently combines the advantages of social learning and intrinsic motivation and benefits from human demonstration properties to learn how to produce varied outcomes in the environment, while developing more precise control policies in large spaces.

关键词： Active learning Intrinsic motivation Exploration Motor skill learning Inverse model programming by demonstration Learning from demonstration Imitation

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Ensuring kinetostatic consistency in observation of human manipulation

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ROBOTICS AND AUTONOMOUS SYSTEMS 2013年第5期61卷 545-553页

作者： Falco, Pietro Natale, Ciro Dillmann, Ruediger Univ Naples 2 Dipartimento Ingn Ind & Informaz I-81031 Aversa Italy Karlsruhe Inst Technol Inst Anthropomat D-76131 Karlsruhe Germany

The aim of this paper is to present a method to guarantee the kinetostatic consistency in observation of human manipulation, i.e. the consistency between the observed hand posture and the tactile information on the contact between the fingertips and the objects. The core idea of the proposed algorithm is to compare the fingertip contact information, obtained by tactile sensors, with the contact information computed in a virtual environment, that reproduces the real environment where the observation is carried out. In case the estimation of the joint angles and the relative pose between the hand and the object are not consistent, a correction of the hand posture is computed. For some tasks, collisions might occur between parts of the hand (e.g. palm) and the grasped object. To handle this problem, the corrected hand posture is computed by adopting a closed loop inverse kinematic (CLIK) approach that exploits the redundant Degrees of Freedom (DoFs) of the hand. The algorithm has been designed to work on-line. This feature is particularly important for programming by demonstration (PbD) applications, since it allows the trainer to actively adapt the demonstration to measurement noise and model errors. The effectiveness of the proposed method has been tested in five different tasks: grasping a cup, unscrewing a bottle, grasping a plate, grasping a ketchup bottle, and grasping a measuring cup. (C) 2012 Elsevier B.V. All rights reserved.

关键词： programming by demonstration Human manipulation On-line multimodal observation Inverse Kinematics

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Generalization of orientation trajectories and force-torque profiles for robotic assembly

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ROBOTICS AND AUTONOMOUS SYSTEMS 2017年 98卷 333-346页

作者： Kramberger, Aljaz Gams, Andrej Nemec, Bojan Chrysostomou, Dimitrios Madsen, Ole Ude, Ales Jozef Stefan Inst Dept Automat Biocybernet & Robot Humanoid & Cognit Robot Lab Jamova Cesta 39 Ljubljana 1000 Slovenia Aalborg Univ Dept Mech & Mfg Engn Robot & Automat Grp Fibigerstraede 16 DK-9220 Aalborg Denmark

A typical robot assembly operation involves contacts with the parts of the product to be assembled and consequently requires the knowledge of not only position and orientation trajectories but also the accompanying force-torque profiles for successful performance. To learn the execution of assembly operations even when the geometry of the product varies across task executions, the robot needs to be able to adapt its motion based on a parametric description of the current task condition, which is usually provided by geometrical properties of the parts involved in the assembly. In our previous work we showed how positional control policies can be generalized to different task conditions. In this paper we propose a complete methodology to generalize also the orientational trajectories and the accompanying force-torque profiles to compute the necessary control policy for a given condition of the assembly task. Our method is based on statistical generalization of successfully recorded executions at different task conditions, which are acquired by kinesthetic guiding. The parameters that describe the varying task conditions define queries into the recorded training data. To improve the execution of the skill after generalization, we combine the proposed approach with an adaptation method, thus enabling the refinement of the generalized assembly operation. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Trajectory generalization Trajectory adaptation programming by demonstration

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Reinforcement learning for imitating constrained reaching movements

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ADVANCED ROBOTICS 2007年第13期21卷 1521-1544页

作者： Guenter, Florent Hersch, Micha Calinon, Sylvain Billard, Aude Ecole Polytech Fed Lausanne LASA Lab CH-1015 Lausanne Switzerland

The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots such that it can be accomplished by anyone. When a demonstrator teaches a task to a robot, he/she shows some ways of fulfilling the task, but not all the possibilities. The robot must then be able to reproduce the task even when unexpected perturbations occur. In this case, it has to learn a new solution. Here, we describe a system to teach the robot constrained reaching tasks. Our system is based on a dynamic system generator modulated by a learned speed trajectory. This system is combined with a reinforcement learning module to allow the robot to adapt the trajectory when facing a new situation, e.g., in the presence of obstacles.

关键词： programming by demonstration reinforcement learning dynamical systems Gaussian mixture model

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Humanoid Tactile Gesture Production using a Hierarchical SOM-based Encoding

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IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT 2014年第2期6卷 153-167页

作者： Pierris, Georgios Dahl, Torbjorn S. Univ Wales Cognit Robot Res Ctr Newport NP18 3QT Gwent Wales Univ Plymouth Cognit Inst Plymouth 03264 Devon England

The existence of cortical hierarchies has long since been established and the advantages of hierarchical encoding of sensor-motor data for control, have long been recognized. Less well understood are the developmental processes whereby such hierarchies are constructed and subsequently used. This paper presents a new algorithm for encoding sequential sensor and actuator data in a dynamic, hierarchical neural network that can grow to accommodate the length of the observed interactions. The algorithm uses a developmental robotics methodology as it extends the Constructivist Learning Architecture, a computational theory of infant cognitive development. This paper presents experimental data demonstrating how the extended algorithm goes beyond the original theory by supporting goal oriented control. The domain studied is the encoding and reproduction of tactile gestures in humanoid robots. In particular, we present results from using a programming by demonstration approach to encode a stroke gesture. Our results demonstrate how the novel encoding enables a Nao humanoid robot with a touch sensitive fingertip to successfully encode and reproduce a stroke gesture in the presence of perturbations from internal and external forces.

关键词： Artificial neural networks programming by demonstration tactile gestures

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Human-robot interaction review and challenges on task planning and programming

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2016年第8期29卷 916-931页

作者： Tsarouchi, Panagiota Makris, Sotiris Chryssolouris, George Univ Patras Dept Mech Engn & Aeronaut Lab Mfg Syst & Automat Patras 26500 Greece

The wide interest of research and industry in the human-robot interaction (HRI) related topics is proportional to the increased productivity and flexibility of the production lines, as it combines human and robot capabilities. This paper presents a review of recent research and progress on HRI, related to task planning/coordination and programming with emphasis on the manufacturing/production environment. Human-robot task allocation and scheduling, metrics for HRI, as well as the social aspects are reviewed. The role of digital human modelling systems for human-robot task planning related issues is also discussed. The process of learning by demonstration as well as the instructive systems is reviewed, focussing mainly on programming through visual guidance and imitation, voice commands and haptic interaction. The aspect of physical HRI as well as the safety related issues are also discussed. Additionally, a survey on multimodal communication frameworks is presented. Challenges encountered and directions for future research are discussed.

关键词： human-robot interaction programming by demonstration learning human-computer interaction robot applications robotic cells

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Improved Generalization of Probabilistic Movement Primitives for Manipulation Trajectories

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第1期9卷 287-294页

作者： Yao, Xueyang Chen, Yinghan Tripp, Bryan Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada

Imitation learning methods have proven effective in learning robotic tasks by leveraging multiple human-controlled demonstrations. However, existing approaches often struggle to generalize across a wide range of tasks, such as extrapolating to unseen object locations, incorporating via-point modulation, accurately modeling orientation, handling trajectories with multiple options, and capturing aiming actions. In this study, we propose a novel framework that combines ideas from task-parameterized Gaussian mixture models and probabilistic movement primitives to address these limitations and satisfy all the aforementioned properties within a single framework. We conduct comprehensive evaluations of our approach on four real-life tasks: pick-and-place, water pouring, shooting a hockey puck into a net, and sweeping.

关键词： programming by demonstration imitation learning few-shot learning probabilistic movement primitives task parameterized Gaussian mixture models

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Skip Blocks: Reusing Execution History to Accelerate Web Scripts

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2017年第OOPSLA期1卷 1-28页

作者： Chasins, Sarah Bodik, Rastislav Univ Calif Berkeley Berkeley CA 94720 USA Univ Washington Seattle WA 98195 USA

With more and more web scripting languages on offer, programmers have access to increasing language support for web scraping tasks. However, in our experiences collaborating with data scientists, we learned that two issues still plague long-running scraping scripts: i) When a network or website goes down mid-scrape, recovery sometimes requires restarting from the beginning, which users find frustratingly slow. ii) Websites do not offer atomic snapshots of their databases;they update their content so frequently that output data is cluttered with slight variations of the same information - e.g., a tweet from profile 1 that is retweeted on profile 2 and scraped from both profiles, once with 52 responses then later with 53 responses. We introduce the skip block, a language construct that addresses both of these disparate problems. Programmers write lightweight annotations to indicate when the current object can be considered equivalent to a previously scraped object and direct the program to skip over the scraping actions in the block. The construct is hierarchical, so programs can skip over long or short script segments, allowing adaptive reuse of prior work. After network and server failures, skip blocks accelerate failure recovery by 7.9x on average. Even scripts that do not encounter failures benefit;because sites display redundant objects, skipping over them accelerates scraping by up to 2.1x. For longitudinal scraping tasks that aim to fetch only new objects, the second run exhibits an average speedup of 5.2x. Our small user study reveals that programmers can quickly produce skip block annotations.

关键词： Web Scraping Incremental Scraping programming by demonstration End-User programming

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Evolving behavior sequences for a humanoid entertainment robot

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ARTIFICIAL LIFE AND ROBOTICS 2010年第3期15卷 341-346页

作者： Lee, Wei-Po Jong, Jih-Shiou Yang, Tsung-Hsien Natl Sun Yat Sen Univ Dept Informat Management Kaohsiung 80424 Taiwan

One of the most important issues in developing an entertainment robot is human-robot interaction, in which the robot is expected to learn new behaviors specified by the user. In this article we present an imitation-based mechanism to support robot learning, and use evolutionary computing to learn new behavior sequences. We also propose several advanced techniques at the task level and the computational level to evolve complex sequences. To evaluate our approach, we use it to evolve different behaviors for a humanoid robot. The results show the promise of our approach.

关键词： Entertainment robot Humanoid robot programming by demonstration Genetic algorithm

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