Specifying Dual-Arm Robot Planning Problems Through Natural Language and Demonstration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337147" target="_blank" >RIV/68407700:21730/19:00337147 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/LRA.2019.2898714" target="_blank" >https://doi.org/10.1109/LRA.2019.2898714</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/LRA.2019.2898714" target="_blank" >10.1109/LRA.2019.2898714</a>
Alternative languages
Result language
angličtina
Original language name
Specifying Dual-Arm Robot Planning Problems Through Natural Language and Demonstration
Original language description
Multi-modal robot programming with natural language and demonstration is a promising technique for efficient teaching of manipulation tasks in industrial environments. In particular, with modern dual-arm robots designed to quickly take over tasks at typical industrial workbenches, the direct teaching of task sequences hardly utilizes the robots' capabilities. We, therefore, propose a two-staged approach that combines natural language instructions and demonstration with simultaneous task allocation and motion scheduling based on constraint programming. Instead of providing a task description and demonstrations that are replayed to a large extent, the user describes tasks to be scheduled with all relevant constraints and demonstrates relevant locations relative to workpieces and other objects. With explicitly stated constraints on the partial ordering of tasks, the solver allocates the tasks to the robot arms and schedules them in time while avoiding self-collisions and reducing the makespan in our experiment by 33%. The linguistic concepts of naming and grouping enable systematic reuse of sub-task ensembles. The proposed approach is evaluated with four variants of a glueing use-case from furniture assembly in user studies with ten participants. In these user studies, we observed a speed-up for the task definition of more than six times compared to a textual specification of the planning problems using the Python-based planner API.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50103 - Cognitive sciences
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Robotics and Automation Letters
ISSN
2377-3766
e-ISSN
2377-3766
Volume of the periodical
4
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
2622-2629
UT code for WoS article
000466928400004
EID of the result in the Scopus database
2-s2.0-85065464850