scholarly journals Semantic Linking Maps for Active Visual Object Search

Author(s):  
Zhen Zeng ◽  
Adrian Rofer ◽  
Odest Chadwicke Jenkins
Author(s):  
Zhen Zeng ◽  
Adrian Röfer ◽  
Odest Chadwicke Jenkins

We aim for mobile robots to function in a variety of common human environments, which requires them to efficiently search previously unseen target objects. We can exploit background knowledge about common spatial relations between landmark objects and target objects to narrow down search space. In this paper, we propose an active visual object search strategy method through our introduction of the Semantic Linking Maps (SLiM) model. SLiM simultaneously maintains the belief over a target object's location as well as landmark objects' locations, while accounting for probabilistic inter-object spatial relations. Based on SLiM, we describe a hybrid search strategy that selects the next best view pose for searching for the target object based on the maintained belief. We demonstrate the efficiency of our SLiM-based search strategy through comparative experiments in simulated environments. We further demonstrate the real-world applicability of SLiM-based search in scenarios with a Fetch mobile manipulation robot.


2015 ◽  
Vol 77 (8) ◽  
pp. 2684-2693 ◽  
Author(s):  
Sarah Chabal ◽  
Scott R. Schroeder ◽  
Viorica Marian
Keyword(s):  

2020 ◽  
Vol 5 (2) ◽  
pp. 1279-1286
Author(s):  
Raphael Druon ◽  
Yusuke Yoshiyasu ◽  
Asako Kanezaki ◽  
Alassane Watt

2013 ◽  
Vol 29 (4) ◽  
pp. 986-1002 ◽  
Author(s):  
Alper Aydemir ◽  
Andrzej Pronobis ◽  
Moritz Gobelbecker ◽  
Patric Jensfelt

2018 ◽  
Author(s):  
Noam Roth ◽  
Nicole C. Rust

ABSTRACTSearching for a specific visual object requires our brain to compare the items in view with a remembered representation of the sought target to determine whether a target match is present. This comparison is thought to be implemented, in part, via the combination of top-down modulations reflecting target identity with feed-forward visual representations. However, it remains unclear whether top-down signals are integrated at a single locus within the ventral visual pathway (e.g. V4) or at multiple stages (e.g. both V4 and inferotemporal cortex, IT). To investigate, we recorded neural responses in V4 and IT as rhesus monkeys performed a task that required them to identify when a target object appeared across variation in position, size and background context. We found non-visual, task-specific signals in both V4 and IT. To evaluate whether V4 was the only locus for the integration of top-down signals, we evaluated several feed-forward accounts of processing from V4 to IT, including a model in which IT preferentially sampled from the best V4 units and a model that allowed for nonlinear IT computation. IT task-specific modulation was not accounted for by any of these feed-forward descriptions, suggesting that during object search, top-down signals are integrated directly within IT.NEW & NOTEWORTHYTo find specific objects, the brain must integrate top-down, target-specific signals with visual information about objects in view. However, the exact route of this integration in the ventral visual pathway is unclear. In the first study to systematically compare V4 and IT during an invariant object search task, we demonstrate that top-down signals found in IT cannot be described as being inherited from V4, but rather must be integrated directly within IT itself.


2019 ◽  
Vol 122 (6) ◽  
pp. 2522-2540 ◽  
Author(s):  
Noam Roth ◽  
Nicole C. Rust

Searching for a specific visual object requires our brain to compare the items in view with a remembered representation of the sought target to determine whether a target match is present. This comparison is thought to be implemented, in part, via the combination of top-down modulations reflecting target identity with feed-forward visual representations. However, it remains unclear whether top-down signals are integrated at a single locus within the ventral visual pathway (e.g., V4) or at multiple stages [e.g., both V4 and inferotemporal cortex (IT)]. To investigate, we recorded neural responses in V4 and IT as rhesus monkeys performed a task that required them to identify when a target object appeared across variation in position, size, and background context. We found nonvisual, task-specific signals in both V4 and IT. To evaluate whether V4 was the only locus for the integration of top-down signals, we evaluated several feed-forward accounts of processing from V4 to IT, including a model in which IT preferentially sampled from the best V4 units and a model that allowed for nonlinear IT computation. IT task-specific modulation was not accounted for by any of these feed-forward descriptions, suggesting that during object search, top-down signals are integrated directly within IT. NEW & NOTEWORTHY To find specific objects, the brain must integrate top-down, target-specific signals with visual information about objects in view. However, the exact route of this integration in the ventral visual pathway is unclear. In the first study to systematically compare V4 and inferotemporal cortex (IT) during an invariant object search task, we demonstrate that top-down signals found in IT cannot be described as being inherited from V4 but rather must be integrated directly within IT itself.


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