From High-Level Task Descriptions to Executable Robot Code

Stenmark, Maj; Malec, Jacek; Stolt, Andreas

doi:10.1007/978-3-319-11310-4_17

Cited by 15 publications

(13 citation statements)

References 18 publications

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“…Other tools for high-level programming often assume an existing library of robot skills, e.g., tools supporting natural language instructions as for example presented by Stenmark et al [32] need basic knowledge of objects (and their coordinate frames) and that it is possible to update and refine solutions suggested by a learning and reasoning system to industrially adequate robustness and precision. Hence, we see our interface as appropriate to support even non-expert users in handling the construction of such basic knowledge items as well as in updating and refining existing solutions.…”

Section: Resultsmentioning

confidence: 99%

“…We identified several issues during the programming process, which are mostly related to the traditional programming interfaces and assumed workflow for the YuMi [34,37]. From those issues, we derived requirements for the development of a programming interface that supports (and is supported by) our underlying architecture for skill representation and robot code generation [32].…”

Section: Case Studiesmentioning

confidence: 99%

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Simplified Programming of Re-usable Skills on a Safe Industrial Robot

Stenmark

Haaae

Topp

2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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This paper presents a study on iconic programming support for mainly position-based lead-through programming of an ABB YuMi collaborative robot. A prototype tool supporting a hybrid programming and execution mode was developed and evaluated with 21 non-expert users with varying programming and robotics experience. We also present a comparison of the programming times for an expert robot programmer using traditional tools versus the new tool. The expert programmed the same tasks in 1/5 of the time compared to traditional tools and the non-experts were able to program and debug a LEGO building task using the robot within 30 minutes.

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Section: Resultsmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

Simplified Programming of Re-usable Skills on a Safe Industrial Robot

Stenmark

Haaae

Topp

2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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“…Coordination between the layers is a complex problem, especially considering the difference in their contexts. Stenmark et al proposed the integration of high-level task description with action execution [46]. However, coordination of the tasks was not a goal of this work.…”

Section: ) Structures and Behaviour Models For Robot Systemsmentioning

confidence: 99%

Scheduling of a Robot’s Tasks With the TaskER Framework

Dudek

Winiarski

2020

IEEE Access

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Robots, in contrast to typical computational systems, affect the physical environment directly. Therefore, other assumptions must be considered for task management procedures in these system types. Robots coexist with humans in the environment and act upon potentially dangerous objects (e.g., a cooker); hence, extra safety procedures in robot task harmonisation must be ensured. Additionally, an algorithm that schedules tasks for a robot and optimises the robot's operation needs to consider the robot motion time, dynamics of the physical processes, changes in the robot user preferences and changes in the environment made by other habitants. In this article, we investigate the problem of switching between various independent tasks safely and state requirements for a control system resolving it. The tasks are uploaded to a store, launched on a robot at the user's request (similar to smartphone applications) and scheduled following a configurable algorithm. Furthermore, we design a model of systems satisfying the requirements. The systems are structured with agents of different classes. We propose a task-switching procedure and dedicated states of the finite-state machines describing the operation of the agents. Finally, we present a TaskER framework implementing the model, and we verify the model through the execution of an exemplary system in scenarios showing the benefits of the model implementation. As a result of our approach application, the robot tasks can be safely interrupted, postponed, resumed, and potential danger (e.g., leaving a cooker on for a long time) can be minimised.

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“…Wächter et al (2016) show a use-case of transferring a state chart to a different robot. Stenmark et al (2015) talk about skill reuse, but only in the sense of reparametrization of the previously developed skill by a user, without providing an explicit framework for choosing the skills for reuse. By contrast, our study addresses the reuse of previous examples of execution based not only on action but also on object similarity, with the aim to reduce the user's parametrization effort.…”

Section: Comparison With the State Of The Artmentioning

confidence: 99%

Cut & recombine: reuse of robot action components based on simple language instructions

Tamošiūnaitė

Aein

Braun

et al. 2019

The International Journal of Robotics Research

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Human beings can generalize from one action to similar ones. Robots cannot do this and progress concerning information transfer between robotic actions is slow. We have designed a system that performs action generalization for manipulation actions in different scenarios. It relies on an action representation for which we perform code-snippet replacement, combining information from different actions to form new ones. The system interprets human instructions via a parser using simplified language. It uses action and object names to index action data tables (ADTs), where execution-relevant information is stored. We have created an ADT database from three different sources (KUKA LWR, UR5, and simulation) and show how a new ADT is generated by cutting and recombining data from existing ADTs. To achieve this, a small set of action templates is used. After parsing a new instruction, index-based searching finds similar ADTs in the database. Then the action template of the new action is matched against the information in the similar ADTs. Code snippets are extracted and ranked according to matching quality. The new ADT is created by concatenating code snippets from best matches. For execution, only coordinate transforms are needed to account for the poses of the objects in the new scene. The system was evaluated, without additional error correction, using 45 unknown objects in 81 new action executions, with 80% success. We then extended the method including more detailed shape information, which further reduced errors. This demonstrates that cut & recombine is a viable approach for action generalization in service robotic applications.

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From High-Level Task Descriptions to Executable Robot Code

Cited by 15 publications

References 18 publications

Simplified Programming of Re-usable Skills on a Safe Industrial Robot

Simplified Programming of Re-usable Skills on a Safe Industrial Robot

Scheduling of a Robot’s Tasks With the TaskER Framework

Cut & recombine: reuse of robot action components based on simple language instructions

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