Analysis of Methods for Incremental Policy Refinement by Kinesthetic Guidance

Simonič, Mihael; Petrič, Tadej; Ude, Aleš; Nemec, Bojan

doi:10.1007/s10846-021-01328-y

Cited by 16 publications

(15 citation statements)

References 33 publications

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“…We first displaced the target position by 2 mm in the negative y direction so that the insertion failed. As the exception strategy for this case has not yet been programmed, the operator demonstrated how to resume the operation and resolve the issue using iterative kinesthetic guidance [ 7 ]. When the target was displaced by the same offset again, the robot was able to resolve the problem.…”

Section: Resultsmentioning

confidence: 99%

“…In the event of an error, the system stops, and the robot switches to gravity compensation mode. Using incremental kinesthetic guidance [ 7 ], the operator performs a sequence of movements to allow the continuation of regular operation. First, the robot builds a database of corrective actions and associates them with the detected error contexts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determining Exception Context in Assembly Operations from Multimodal Data

Simonič

Hrovat

Džeroski

et al. 2022

Sensors

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Robot assembly tasks can fail due to unpredictable errors and can only continue with the manual intervention of a human operator. Recently, we proposed an exception strategy learning framework based on statistical learning and context determination, which can successfully resolve such situations. This paper deals with context determination from multimodal data, which is the key component of our framework. We propose a novel approach to generate unified low-dimensional context descriptions based on image and force-torque data. For this purpose, we combine a state-of-the-art neural network model for image segmentation and contact point estimation using force-torque measurements. An ensemble of decision trees is used to combine features from the two modalities. To validate the proposed approach, we have collected datasets of deliberately induced insertion failures both for the classic peg-in-hole insertion task and for an industrially relevant task of car starter assembly. We demonstrate that the proposed approach generates reliable low-dimensional descriptors, suitable as queries necessary in statistical learning.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determining Exception Context in Assembly Operations from Multimodal Data

Simonič

Hrovat

Džeroski

et al. 2022

Sensors

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“…The approach is well suited when multiple demonstrations are compared for the extraction of relevant information for learning. Following the AL-DMPs idea, Simonič et al (2021) introduced a constant speed DMPs to fully decouple the spatial and temporal part of the task. Pahic et al (2021) used deep NN to map images into spatial paths represented by AL-DMPs.…”

Section: Dmp Extensionsmentioning

confidence: 99%

Dynamic movement primitives in robotics: A tutorial survey

Saveriano,

Abu-Dakka,

Kramberger

et al. 2023

The International Journal of Robotics Research

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Biological systems, including human beings, have the innate ability to perform complex tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to comprehend and formally define this innate characteristic. The idea, supported by several experimental findings, that biological systems are able to combine and adapt basic units of motion into complex tasks finally leads to the formulation of the motor primitives’ theory. In this respect, Dynamic Movement Primitives (DMPs) represent an elegant mathematical formulation of the motor primitives as stable dynamical systems and are well suited to generate motor commands for artificial systems like robots. In the last decades, DMPs have inspired researchers in different robotic fields including imitation and reinforcement learning, optimal control, physical interaction, and human–robot co-working, resulting in a considerable amount of published papers. The goal of this tutorial survey is two-fold. On one side, we present the existing DMP formulations in rigorous mathematical terms and discuss the advantages and limitations of each approach as well as practical implementation details. In the tutorial vein, we also search for existing implementations of presented approaches and release several others. On the other side, we provide a systematic and comprehensive review of existing literature and categorize state-of-the-art work on DMP. The paper concludes with a discussion on the limitations of DMPs and an outline of possible research directions.

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“…It provides a software and hardware framework that includes both front-end and back-end solutions to integrate programming by demonstration paradigm into an effective system for programming force-based skills. The proposed approach is based on the manual guidance of a robot by a human teacher to collect the data needed to specify force-based skills and consists of two main components: virtual mechanisms and incremental policy refinement [48]. Among the common industrial tasks that can be automated this way are grinding and polishing.…”

Section: Robot Programming Of Hard To Transfer Tasks By Manual Guidancementioning

confidence: 99%

Technology Modules Providing Solutions for Agile Manufacturing

Deniša,

Ude,

Simonič

et al. 2023

Machines

Self Cite

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In this paper, we address the most pressing challenges faced by the manufacturing sector, particularly the manufacturing of small and medium-sized enterprises (SMEs), where the transition towards high-mix low-volume production and the availability of cost-effective solutions are crucial. To overcome these challenges, this paper presents 14 innovative solutions that can be utilized to support the introduction of agile manufacturing processes in SMEs. These solutions encompass a wide range of key technologies, including reconfigurable fixtures, low-cost automation for printed circuit board (PCB) assembly, computer-vision-based control, wireless sensor networks (WSNs) simulations, predictive maintenance based on Internet of Things (IoT), virtualization for operator training, intuitive robot programming using virtual reality (VR), autonomous trajectory generation, programming by demonstration for force-based tasks, on-line task allocation in human–robot collaboration (HRC), projector-based graphical user interface (GUI) for HRC, human safety in collaborative work cells, and integration of automated ground vehicles for intralogistics. All of these solutions were designed with the purpose of increasing agility in the manufacturing sector. They are designed to enable flexible and modular manufacturing systems that are easy to integrate and use while remaining cost-effective for SMEs. As such, they have a high potential to be implemented in the manufacturing industry. They can be used as standalone modules or combined to solve a more complicated task, and contribute to enhancing the agility, efficiency, and competitiveness of manufacturing companies. With their application tested in industrially relevant environments, the proposed solutions strive to ensure practical implementation and real-world impact. While this paper presents these solutions and gives an overview of their methodologies and evaluations, it does not go into their details. It provides summaries of comprehensive and multifaceted solutions to tackle the evolving needs and demands of the manufacturing sector, empowering SMEs to thrive in a dynamic and competitive market landscape.

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Analysis of Methods for Incremental Policy Refinement by Kinesthetic Guidance

Cited by 16 publications

References 33 publications

Determining Exception Context in Assembly Operations from Multimodal Data

Determining Exception Context in Assembly Operations from Multimodal Data

Dynamic movement primitives in robotics: A tutorial survey

Technology Modules Providing Solutions for Agile Manufacturing

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