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Visual Representations for Semantic Target Driven Navigation [article]

Arsalan Mousavian, Alexander Toshev, Marek Fiser, Jana Kosecka, Ayzaan Wahid, James Davidson
2019 arXiv   pre-print
What is a good visual representation for autonomous agents?  ...  We address this question in the context of semantic visual navigation, which is the problem of a robot finding its way through a complex environment to a target object, e.g. go to the refrigerator.  ...  CONCLUSION We have demonstrated the use of semantic visual representations obtained from state-of-the-art detectors and segmentors for target driven visual navigation.  ... 
arXiv:1805.06066v3 fatcat:lsqm7gowd5ck7nw4gpw7htrj24

Workshop Summary

Valentina Ivanova, Patrick Lambrix, Steffen Lohmann, Catia Pesquita
2016 International Semantic Web Conference  
Visualizations are targeted to varying user groups, since individuals possess diverse backgrounds and differ in navigational strategies and abilities; they seek to fulfill different information needs and  ...  Navigating an information space is indispensable for understanding its content and structure, it is an activity accompanying higher-level tasks.  ...  the last session-Visualization in Semantic Annotation-is composed of two talks presenting approaches for semantic annotation in order to improve navigation and exploration.  ... 
dblp:conf/semweb/IvanovaLLP16 fatcat:ato24uxhljd5vgsd4r6ftjew6u

Simultaneous Mapping and Target Driven Navigation [article]

Georgios Georgakis, Yimeng Li, Jana Kosecka
2019 arXiv   pre-print
This work presents a modular architecture for simultaneous mapping and target driven navigation in indoors environments.  ...  We demonstrate that the use of semantic information improves localization accuracy and the ability of storing spatial semantic map aids the target driven navigation policy.  ...  The experiments on AVD and Matterport3D environments demonstrate that our approach outperforms only RGB baselines for the task of localization, and non-mapping baselines for the target-driven navigation  ... 
arXiv:1911.07980v1 fatcat:n2onyhoebzapri7bx7qjjwzo5y

GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment [article]

Xin Ye, Zhe Lin, Joon-Young Lee, Jianming Zhang, Shibin Zheng and Yezhou Yang
2019 arXiv   pre-print
While scene-driven or recognition-driven visual navigation has been widely studied, prior efforts suffer severely from the limited generalization capability.  ...  We study the problem of learning a generalizable action policy for an intelligent agent to actively approach an object of interest in an indoor environment solely from its visual inputs.  ...  RELATED WORK Target-driven visual navigation.  ... 
arXiv:1809.08287v2 fatcat:3up3mviorjflpmo4eogxotjfdq

NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations

Qiaoyun Wu, Dinesh Manocha, Jun Wang, Kai Xu
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
First, the latent distribution is conditioned on current observations and the target view, leading to a model-based, target-driven navigation.  ...  We propose improving the cross-target and cross-scene generalization of visual navigation through learning an agent that is guided by conceiving the next observations it expects to see.  ...  Acknowledgments We thank Xingyu Xie for fruitful discussions in the early stage of this project. This work was supported in part  ... 
doi:10.1609/aaai.v34i06.6556 fatcat:mtp5nrfxuze5fil5ltcuo3kcwi

Learning Object Relation Graph and Tentative Policy for Visual Navigation [article]

Heming Du, Xin Yu, Liang Zheng
2020 arXiv   pre-print
Target-driven visual navigation aims at navigating an agent towards a given target based on the observation of the agent.  ...  In this task, it is critical to learn informative visual representation and robust navigation policy.  ...  Previous Proposed Method Our goal is to introduce an informative visual representation and a failure-aware navigation policy for a target-driven visual navigation system.  ... 
arXiv:2007.11018v1 fatcat:73ftebycd5hvpkibloh2r3m45e

Object-oriented Targets for Visual Navigation using Rich Semantic Representations [article]

Jean-Benoit Delbrouck, Stéphane Dupont
2018 arXiv   pre-print
In this paper, we propose to tackle the visual navigation problem using rich semantic representations of the observed scene and object-oriented targets to train an agent.  ...  When searching for an object humans navigate through a scene using semantic information and spatial relationships.  ...  [12] proposed a deep reinforcement learning framework for target-driven visual navigation. As input to the model, only the target frame is given without any other priors about the environment.  ... 
arXiv:1811.09178v2 fatcat:isc3ox3i5jd47pgjqvosrefavm

Reinforcement Learning-based Visual Navigation with Information-Theoretic Regularization [article]

Qiaoyun Wu, Kai Xu, Jun Wang, Mingliang Xu, Xiaoxi Gong, Dinesh Manocha
2022 arXiv   pre-print
To enhance the cross-target and cross-scene generalization of target-driven visual navigation based on deep reinforcement learning (RL), we introduce an information-theoretic regularization term into the  ...  This way, the agent learns to understand the causality between navigation actions and the changes in its observations, which allows the agent to predict the next action for navigation by comparing the  ...  TARGET-DRIVEN VISUAL NAVIGATION In this section, we begin by outlining the target-driven visual navigation task.  ... 
arXiv:1912.04078v7 fatcat:swswxqspq5farf7ks4oncz4pwy

Learning View and Target Invariant Visual Servoing for Navigation [article]

Yimeng Li, Jana Kosecka
2020 arXiv   pre-print
In this paper we propose to learn viewpoint invariant and target invariant visual servoing for local mobile robot navigation; given an initial view and the goal view or an image of a target, we train deep  ...  The advances in deep reinforcement learning recently revived interest in data-driven learning based approaches to navigation.  ...  Related problem of semantic target driven navigation was considered by [10] , [11] where object is specified as an image or as an semantic category [12] considering mid-range navigation tasks and  ... 
arXiv:2003.02327v1 fatcat:oaqmy4bivfbebogjhircagmkoe

NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations [article]

Qiaoyun Wu, Dinesh Manocha, Jun Wang, Kai Xu
2022 arXiv   pre-print
First, the latent distribution is conditioned on current observations and the target view, leading to a model-based, target-driven navigation.  ...  We propose improving the cross-target and cross-scene generalization of visual navigation through learning an agent that is guided by conceiving the next observations it expects to see.  ...  Acknowledgments We thank Xingyu Xie for fruitful discussions in the early stage of this project.  ... 
arXiv:1906.07207v4 fatcat:xwjnp5iutbdr7d7iwprpqjaft4

Model-agnostic Metalearning Based Text-driven Visual Navigation Model for Unfamiliar Tasks

Tianfang Xue, Haibin Yu
2020 IEEE Access  
TEXT-DRIVEN VISUAL NAVIGATION MODEL In this section, we will formally give a thorough introduction of our adaptive text-driven navigation model.  ...  TARGET-DRIVEN NAVIGATION PERFORMANCE We first evaluate the basic target-driven navigation performance by performing navigation tasks with other baselines, to ensure that the basic navigation accuracy has  ... 
doi:10.1109/access.2020.3023014 fatcat:fpvxwp3jpbgq7fnpem3m6brld4

Developing Semantic Rich Internet Applications Using a Model-Driven Approach [chapter]

Jesús M. Hermida, Santiago Meliá, Andrés Montoyo, Jaime Gómez
2011 Lecture Notes in Computer Science  
Semantic Web technologies can be the key for opening RIA contents to any client.  ...  In this context, this paper focuses on two of these: Rich Internet Applications (RIA) and the Semantic Web.  ...  Orchestration models for automatically generating a new semantic representation of the RIA UI called Visualization Ontology Model.  ... 
doi:10.1007/978-3-642-24396-7_16 fatcat:r5uif2tgczh3bfzhzws6yqb3me

Attention to Action: Leveraging Attention for Object Navigation

Shi Chen, Qi Zhao
2021 British Machine Vision Conference  
Our experiments show significant improvements in navigation across various types of unseen environments with known and unknown semantics.  ...  Instead of working conventionally as a weighted map for aggregating visual features, the new attention is defined as a compact intermediate state connecting visual observations and action.  ...  We study how to exploit attention for object navigation and develop a novel attention-driven navigation agent (ANA).  ... 
dblp:conf/bmvc/ChenZ21 fatcat:rxgqls6qtffsvbv3j62jmpk52e

Situational Fusion of Visual Representation for Visual Navigation [article]

Bokui Shen, Danfei Xu, Yuke Zhu, Leonidas J. Guibas, Li Fei-Fei, Silvio Savarese
2021 arXiv   pre-print
A complex visual navigation task puts an agent in different situations which call for a diverse range of visual perception abilities.  ...  For example, to "go to the nearest chair", the agent might need to identify a chair in a living room using semantics, follow along a hallway using vanishing point cues, and avoid obstacles using depth.  ...  Acknowledgement: We thank Andrey Kurenkov and Ajay Mandlekar for helpful comments.  ... 
arXiv:1908.09073v2 fatcat:zjhb3pft6jhibipvpi5sitlqfa

Neural Topological SLAM for Visual Navigation

Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
To tackle this problem, we design topological representations for space that effectively leverage semantics and afford approximate geometric reasoning.  ...  Experimental study in visually and physically realistic simulation suggests that our method builds effective representations that capture structural regularities and efficiently solve long-horizon navigation  ...  For more complex problems such as target-driven navigation in a novel environment, such purely reactive strategies do not work well [47] , and memory-based policies have been investigated.  ... 
doi:10.1109/cvpr42600.2020.01289 dblp:conf/cvpr/ChaplotS0020 fatcat:5irwrabgtrc6bpqtu37lvcidja
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