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Inferring Compact Representations for Efficient Natural Language Understanding of Robot Instructions
[article]
2019
arXiv
pre-print
Preserved Fulltext
An open problem is then to develop methods capable of producing the most compact environment model sufficient for accurate and efficient natural language understanding. ...
A great deal of attention has been paid to developing models and approximate inference algorithms that improve the efficiency of language understanding. ...
environment representation sufficient for planning and natural language understanding. ...
arXiv:1903.09243v1
fatcat:xxl5ora4zvd3pku7smactjqdxy
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments
[article]
2019
arXiv
pre-print
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Recent advances in data-driven models for grounded language understanding have enabled robots to interpret increasingly complex instructions. ...
Recent semantic mapping methods address partial observability by exploiting language as a sensor to infer a distribution over topological, metric and semantic properties of the environment. ...
The natural language understanding models were trained on a data-augmented corpus of approximately 115 instructions annotated separately for perception, behavior, and map inferences. ...
arXiv:1910.10034v1
fatcat:xvtsqctqu5aq3jl4gl6kkbpyoi
Language-guided Adaptive Perception with Hierarchical Symbolic Representations for Mobile Manipulators
[article]
2019
arXiv
pre-print
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Language is an effective medium for bi-directional communication in human-robot teams. ...
To infer the meaning of many instructions, robots need to construct a model of their surroundings that describe the spatial, semantic, and metric properties of objects from observations and prior information ...
For language to be an effective tool for human-robot teams, robots must understand instructions in the context of its surround- Figure 1 : An example of objects with natural hierarchies. ...
arXiv:1909.09880v1
fatcat:p6ak36k56ra4xmpvpdxpgwmlxi
Language Understanding for Field and Service Robots in a Priori Unknown Environments
2022
Field Robotics
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Natural language provides one such medium, and through significant progress in statistical methods for natural-language understanding, robots are now able to interpret a diverse array of free-form navigation ...
that the algorithm can follow natural-language instructions without prior knowledge of the environment. ...
Natural-Language Understanding The approach to natural-language understanding of robot instructions in this paper relies on variations of the Distributed Correspondence Graph (DCG) (Howard et al., 2014b ...
doi:10.55417/fr.2022040
fatcat:2zcvlzqehfghtlispn3m7dhwy4
Learning models for following natural language directions in unknown environments
2015
2015 IEEE International Conference on Robotics and Automation (ICRA)
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Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. ...
Our method uses this distribution in place of the latent world model and interprets the natural language instruction as a distribution over the intended behavior. ...
ACKNOWLEDGMENTS This work was supported in part by the Robotics Consortium of the U.S. ...
doi:10.1109/icra.2015.7139984
dblp:conf/icra/HemachandraDHRS15
fatcat:fgmwhttnv5e7ffrqqmcvdx24ui
Learning Models for Following Natural Language Directions in Unknown Environments
[article]
2015
arXiv
pre-print
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Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. ...
Our method uses this distribution in place of the latent world model and interprets the natural language instruction as a distribution over the intended behavior. ...
ACKNOWLEDGMENTS This work was supported in part by the Robotics Consortium of the U.S. ...
arXiv:1503.05079v1
fatcat:vqfp5di7ejea7nk5obibvqdgyy
Cloud-Based Probabilistic Knowledge Services for Instruction Interpretation
[chapter]
2017
Springer Proceedings in Advanced Robotics
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As the tasks of autonomous manipulation robots get more complex, the tasking of the robots using natural-language instructions becomes more important. ...
These joint probability distributions are then used to compute the plan instantiation that has the highest probability of producing the intended action given the natural language instruction. ...
In other words, understanding a natural-language instruction for robot execution requires appropriate interpretation and completion. ...
doi:10.1007/978-3-319-60916-4_37
dblp:conf/isrr/NygaB15
fatcat:myzydcewivdbfeyl3nnnauqbqq
What Matters in Language Conditioned Robotic Imitation Learning
[article]
2022
arXiv
pre-print
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A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and specified only via natural language. ...
plans and a self-supervised contrastive loss that aligns video and language representations. ...
However, we expect our model to use the time-dependent representation of the sequence visual observations in order to truly understand the meaning of a language instruction. ...
arXiv:2204.06252v1
fatcat:xnq35sp7xvelpfubinjpraec7a
Approaches for Action Sequence Representation in Robotics: A Review
2018
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Robust representation of actions and its sequences for complex robotic tasks would transform robot's understanding to execute robotic tasks efficiently. ...
In this manuscript, we present a review of literature dealing with representation of action and action sequences for robot task planning and execution. ...
Different combinations of keywords were used: "action sequences", "knowledge representation", "logic", "robot", "natural language processing", "open-source frameworks", "ROS", "visual representation languages ...
doi:10.1109/iros.2018.8594256
dblp:conf/iros/NakawalaGFFM18
fatcat:aamljxaqyvbnvjpoqulgmefc7a
Deep Multimodal Embedding: Manipulating Novel Objects with Point-clouds, Language and Trajectories
[article]
2017
arXiv
pre-print
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A robot operating in a real-world environment needs to perform reasoning over a variety of sensor modalities such as vision, language and motion trajectories. ...
On a large dataset, we achieve significant improvements in both accuracy and inference time over the previous state of the art. ...
The robot must use the combination of its observations of the world and natural language instructions to infer how to manipulate objects. ...
arXiv:1509.07831v2
fatcat:4f5dl4wze5gapeajo5zpvfwlnu
Deep multimodal embedding: Manipulating novel objects with point-clouds, language and trajectories
2017
2017 IEEE International Conference on Robotics and Automation (ICRA)
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A robot operating in a real-world environment needs to perform reasoning over a variety of sensor modalities such as vision, language and motion trajectories. ...
On a large dataset, we achieve significant improvements in both accuracy and inference time over the previous state of the art. ...
The robot must use the combination of its observations of the world and natural language instructions to infer how to manipulate objects. ...
doi:10.1109/icra.2017.7989325
dblp:conf/icra/SungLS17
fatcat:cht7lkjt5zdvxm4jlxi6bbvay4
Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications
2018
Robotics: Science and Systems XIV
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This class of behaviors poses a serious obstacle to existing language understanding for robotics approaches that map to either action sequences or goal state representations. ...
One example of this could be instructing a wheeled robot to "go to the living room but avoid the kitchen," in order to avoid scuffing the floor. ...
APPROACH In order to fully specify our system for converting natural language to robot behavior, we begin by describing our problem setting and clarify its connection to the GLTL semantic representation ...
doi:10.15607/rss.2018.xiv.067
dblp:conf/rss/GopalanAWT18
fatcat:mlhrku6zrzfbbjbco62wbmnsva
Object Graph Networks for Spatial Language Grounding
2019
2019 Digital Image Computing: Techniques and Applications (DICTA)
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Consider a domestic robot being asked to pick up "the cup nearest to the plate". Natural language is an intuitive way for humans to interact with robots. ...
However, enabling robots to comprehend natural language, and correctly interpret spatial references, is challenging for two reasons. ...
The third bypasses intermediate representations and infers actions directly from natural language instruction and observations of the environment using neural networks [25] , [34] . ...
doi:10.1109/dicta47822.2019.8946101
dblp:conf/dicta/HawkinsMDB19
fatcat:pkh22hrgnzdgtmgzufupz5gbdq
Multimodal Binding of Parameters for Task-based Robot Programming Based on Semantic Descriptions of Modalities and Parameter Types
2015
IEEE/RJS International Conference on Intelligent RObots and Systems
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In this paper, we describe our ongoing efforts to design a cognition-enabled industrial robotic workcell, which significantly increases the efficiency of teaching and adapting robot tasks. ...
We have designed a formalism to match task parameter and input modality types, in order to infer suitable means for binding values to those parameters. ...
Some of the missing parameters can be automatically inferred. One aspect of naturally teaching tasks to a robot system is an adequate selection of communication modalities. ...
dblp:conf/iros/PerzyloSPRK15
fatcat:go3qtacxybdojpvcy2vzy5ko5m
Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data
[article]
2020
arXiv
pre-print
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We address this problem by introducing a general purpose technique for "simulation-to-real" transfer in language understanding problems with a delimited set of target behaviors, making it possible to develop ...
To generalize to natural utterances, we automatically find projections of natural language utterances onto the support of the synthetic language, using learned sentence embeddings to define a distance ...
The semantic originally described by Wang et al. for this task was equipped with a "canonical grammar"-a compact set of rules describing a mapping from logical forms to (somewhat stilted) natural language ...
arXiv:2004.13645v1
fatcat:vee34acnwzdhte6e5djherpt6q
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