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programming-by-demonstration of reaching motions-A next-state-planner approach

ROBOTICS AND AUTONOMOUS SYSTEMS 2010年第5期58卷 607-621页

作者： Skoglund, Alexander Iliev, Boyko Palm, Rainer Univ Orebro AASS Learning Syst Lab SE-70182 Orebro Sweden

This paper presents a novel approach to skill acquisition from human demonstration. A robot manipulator with a morphology which is very different from the human arm simply cannot copy a human motion, but has to execute its own version of the skill. When a skill once has been acquired the robot must also be able to generalize to other similar skills, without a new learning process. By using a motion planner that operates in an object-related world frame called hand-state, we show that this representation simplifies skill reconstruction and preserves the essential parts of the skill. (C) 2010 Elsevier B.V. All rights reserved.

关键词： programming-by-demonstration Hand-state Motion planner Fuzzy modeling Correspondence problem

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programming-by-demonstration of Reaching Motions for Robot Grasping

Programming-by-Demonstration of Reaching Motions for Robot G...

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14th International Conference on Advanced Robotics

作者： Skoglund, Alexander Tegin, Johan Iliev, Boyko Palm, Rainer Univ Orebro Sch Sci & Technol Ctr Appl Autonomous Sensor Syst Orebro Sweden Royal Inst Technol KTH Stockholm Sweden

ISBN: (纸本)9781424448555

This paper presents a novel approach to skill modeling acquired from human demonstration. The approach is based on fuzzy modeling and is using a planner for generating corresponding robot trajectories. One of the main challenges stems from the morphological differences between human and robot hand/arm structure, which makes direct copying of human motions impossible in the general case. Thus, the planner works in hand state space, which is defined such that it is perception-invariant and valid for both human and robot hand. We show that this representation simplifies task reconstruction and preserves the essential parts of the task as well as the coordination between reaching and grasping motion. We also show how our approach can generalize observed trajectories based on multiple demonstrations and that the robot can match a demonstrated behavoir, despite morphological differences. To validate our approach we use a general-purpose robot manipulator equipped with an anthropomorphic three-fingered robot hand.

关键词： programming-by-demonstration Hand State Motion Planner Fuzzy Modeling Correspondence Problem

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programming-by-demonstration of Robot Skills using Fuzzy-Time-Modeling

Programming-by-Demonstration of Robot Skills using Fuzzy-Tim...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Palm, Rainer Iliev, Boyko Univ Orebro Dept Technol AASS SE-70182 Orebro Sweden

ISBN: (纸本)9781424465880

Robot skills are motion or grasping primitives from which a complicated robot task consists. Skills can be directly learned and recognized by a technique named programming-by-demonstration. A human operator demonstrates a set of reference skills where his motions are recorded by a data-capturing system and modeled via fuzzy clustering and a Takagi-Sugeno modeling technique. The skill models use the time instants as input and the actions of the operator as outputs. In the recognition phase, the robot identifies the skill that has been shown by the operator in a novel test demonstration. The recognition is done by comparing of the time clusters of the test skill and the reference skills. Finally, using the corresponding reference skill model the robot executes the recognized skill. Skill models can be updated on-line where drastic differences between learned and real world conditions during the execution of skills by the robot are eliminated using the Broyden update formula. This method was extended for fuzzy models especially for time cluster models. The updated model is used for further executions of the same skill by the robot.

关键词： Broyden update formula Takagi-Sugeno modeling technique control engineering computing data-capturing system fuzzy clustering fuzzy set theory fuzzy-time-modeling grasping primitives pattern clustering programming-by-demonstration robot programming robot skills

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Sheepdog, parallel collaborative programming-by-demonstration

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KNOWLEDGE-BASED SYSTEMS 2010年第2期23卷 94-109页

作者： Castelli, Vittorio Bergman, Lawrence Lau, Tessa Oblinger, Daniel IBM Corp TJ Watson Res Ctr Yorktown Hts NY 10598 USA IBM Corp TJ Watson Res Ctr Hawthorne NY 10532 USA IBM Corp Almaden Res Ctr San Jose CA 95120 USA DARPA PTO Arlington VA 22203 USA

We introduce parallel collaborative programming-by-demonstration (PBD) as a principled approach to capturing knowledge on how to perform computer-based procedures by independently recording multiple experts executing these tasks and combining the recordings via a learning algorithm. Traditional PBD has focused on end-user programming for a single user, and does not support parallel collaborative procedure model construction from examples provided by multiple experts. In this paper we discuss how to extend the main aspects of PBD (instrumentation, abstraction, learning, and execution), and we describe the implementation of these extensions in a system called Sheepdog. (C) 2009 Elsevier B.V. All rights reserved.

关键词： programming-by-demonstration Intelligent user interfaces Artificial intelligence Parallel collaborative programming-by-demonstration Architecture for programing-by-demonstration

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programming-by-demonstration and Adaptation of Robot Skills by Fuzzy Time Modeling

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INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS 2014年第1期11卷

作者： Palm, Rainer Iliev, Boyko Univ Orebro Dept Technol AASS SE-70182 Orebro Sweden BAE Syst Bofors AB SE-69180 Karlskoga Sweden

Robot skills are motion or grasping primitives from which a complicated robot task consists. Skills can be directly learned and recognized by a technique named programming-by-demonstration. A human operator demonstrates a set of reference skills where his motions are recorded by a data-capturing system and modeled via fuzzy clustering and a Takagi-Sugeno modeling technique. The skill models use time instants as input and operator actions as outputs. In the recognition phase, the robot identifies the skill shown by the operator in a novel test demonstration. Finally, using the corresponding reference skill model the robot executes the recognized skill. Skill models can be updated online where drastic differences between learned and real world conditions are eliminated using the Broyden update formula. This method was extended for fuzzy models especially for time cluster models.

关键词： Fuzzy modeling time clustering robot skills programming-by-demonstration

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Distributed Augmentation-Based Learning A Learning Algorithm for Distributed Collaborative programming-by-demonstration 07

Distributed Augmentation-Based Learning A Learning Algorithm...

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International Conference on Intelligent User Interfaces

作者： Castelli, Vittorio Bergman, Lawrence IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA

ISBN: (纸本)9781595934819

The learning algorithms used in programming-by-demonstration (PBD) are either on-line and incremental or off-line and batch. Neither category is entirely suitable for capturing know-how from demonstrations in a distributed, collaborative environment, where multiple experts can independently provide examples to improve the model. In this paper we describe Distributed Augmentation-Based Learning (DABL), the first real-time PBD learning algorithm suited for distributed know-how acquisition. DABL is an incremental learning algorithm that uses a version-control-like paradigm to combine independently constructed procedure models. An expert can check out a procedure model from a repository and modify it by means of new demonstrations or by manually editing it. The expert then reconciles the changes with those concurrently made by other experts and checked into the repository. DABL automatically merges the two procedures, learns new decision points based on reconcilable differences, and identifies conflicts where there are multiple valid ways of combining the changes or where the combination produces an invalid model, that is, one that does not lie in the search space of the learning algorithm.

关键词： Example- and demonstration-based interfaces programming-by-demonstration Artificial Intelligence

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Stereoscopic Vision System for Human Gesture Tracking and Robot programming by demonstration

Stereoscopic Vision System for Human Gesture Tracking and Ro...

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International Workshop on Robotics in Smart Manufacturing (WRSM 2013) / 23rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2013)

作者： Ferreira, Marcos Rocha, Luis Costa, Paulo Moreira, A. Paulo INESC-TEC (formerly INESC Porto) Rua Dr. Roberto Frias s/n Campus FEUP Portugal

ISBN: (纸本)9783642392221

This paper presents a framework for robot programming by demonstration using gesture. It is based on a luminous multi-LED marker which is captured by a pair of industrial cameras. Using stereoscopy the marker supplies a complete 6-DoF human gesture tracking output with both position and orientation. Tests show that the developed setup is industrial grade, being precise for many industrial applications and robust particularly to lighting conditions. Attaching the marker to an operator work tool provides an efficient way to track the human movements without further intrusion in the process. The resulting path is used to generate a program for an industrial manipulator ending the cycle in an human-robot skill transfer framework.

关键词： programming-by-demonstration motion tracking artificial vision skill-transfer robotics industrial manipulators

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Combining GRN modeling and demonstration-based programming for robot control

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NEURAL COMPUTING & APPLICATIONS 2011年第6期20卷 909-921页

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

In recent years, gene regulatory networks (GRNs) have been proposed to work as reliable and robust control mechanisms for robots. Because recurrent neural networks (RNNs) have the unique characteristic of presenting system dynamics over time, we thus adopt such kind of network structure and the principles of gene regulation to develop a biologically and computationally plausible GRN model for robot control. To simulate the regulatory effects and to make our model inferable from time-series data, we also implement an enhanced network-learning algorithm to derive network parameters efficiently. In addition, we present a procedure of programming-by-demonstration to collect behavior sequence data of the robot as expression profiles, and then employ our network-modeling framework to infer controllers. To verify the proposed approach, experiments have been conducted, and the results show that our regulatory model can be inferred for robot control successfully.

关键词： Recurrent neural network Gene regulation Time-series data Robot control programming-by-demonstration Imbalance learning

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Combining GRN modeling and demonstration-based programming for robot control

Combining GRN modeling and demonstration-based programming f...

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11th International Conference on Engineering Applications of Neural Networks

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

ISBN: (纸本)3642039685

关键词： Recurrent neural network Gene regulation Time-series data Robot control programming-by-demonstration Imbalance learning

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Augmentation-Based Learning combining observations and user edits for Pro gramming-by-demonstration

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KNOWLEDGE-BASED SYSTEMS 2007年第6期20卷 575-591页

作者： Castelli, Vittorio Oblinger, Daniel Bergman, Lawrence IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA DARPAIIPTO Arlington VA 22203 USA

In this paper, we introduce a new approach to programming-by-demonstration in which the author is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe Augmentation-Based Learning, a new algorithm that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving conflicts in favor of edits. (c) 2007 Elsevier B.V. All rights reserved.

关键词： programming-by-demonstration programming-by-example artificial intelligence example-and demonstration-based interfaces

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