Multimodal cognitive interface for robot navigation

Elmogy, Mohammed; Habel, Christopher; Zhang, Jianwei

doi:10.1007/s10339-010-0386-4

Cited by 4 publications

(3 citation statements)

References 16 publications

(16 reference statements)

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“…Progress in unseen spaces has relied on using constrained subsets of human symbols, or on limiting how far the robot can explore outside of already seen spaces. The guarantee of sequence in route instructions has been exploited with symbol subsets ranging from pointing gestures [13] and input restricted to artificial instruction sets like "$GO()" and "$FOLLOW()" [14], all the way to natural language [43] and free-hand sketches [15]. A limited semantic vocabulary consisting of four prepositions has been used to improve existing navigation performance in observed spaces [11], [44].…”

Section: Use Of Human Symbols In Robot Navigationmentioning

confidence: 99%

Robot Navigation in Unseen Spaces using an Abstract Map

Talbot,

Dayoub,

Corke

et al. 2020

Preprint

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Human navigation in built environments depends on symbolic spatial information which has unrealised potential to enhance robot navigation capabilities. Information sources such as labels, signs, maps, planners, spoken directions, and navigational gestures communicate a wealth of spatial information to the navigators of built environments; a wealth of information that robots typically ignore. We present a robot navigation system that uses the same symbolic spatial information employed by humans to purposefully navigate in unseen built environments with a level of performance comparable to humans. The navigation system uses a novel data structure called the abstract map to imagine malleable spatial models for unseen spaces from spatial symbols. Sensorimotor perceptions from a robot are then employed to provide purposeful navigation to symbolic goal locations in the unseen environment. We show how a dynamic system can be used to create malleable spatial models for the abstract map, and provide an open source implementation to encourage future work in the area of symbolic navigation. Symbolic navigation performance of humans and a robot is evaluated in a real-world built environment. The paper concludes with a qualitative analysis of human navigation strategies, providing further insights into how the symbolic navigation capabilities of robots in unseen built environments can be improved in the future.

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Section: Use Of Human Symbols In Robot Navigationmentioning

confidence: 99%

Robot Navigation in Unseen Spaces using an Abstract Map

Talbot,

Dayoub,

Corke

et al. 2020

Preprint

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“…The spatial information is anchored to the semantic information and the approach is validated via experiments where a mobile robot uses and infers new semantic information from its environment, improving its operation. Similarly Elmogy in [23] investigates how a topological map is generated to describe relationships among features of the environment in a more abstract form to be used in a robot navigation system. A language for instructing the robot to execute a route in an indoor environment is presented where an instruction interpreter processes a route description and generates its equivalent symbolic and topological map representations.…”

Section: Perceptual Anchoringmentioning

confidence: 99%

A Short Review of Symbol Grounding in Robotic and Intelligent Systems

2013

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This paper gives an overview of the research papers published in Symbol Grounding in the period from the beginning of the 21st century up 2012. The focus is in the use of symbol grounding for robotics and intelligent system. The review covers a number of subtopics, that include, physical symbol grounding, social symbol grounding, symbol grounding for vision systems, anchoring in robotic systems, and learning symbol grounding in software systems and robotics. This review is published in conjunction with a special issue on Symbol Grounding in the Künstliche Intelligenz Journal.

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“…The module can further improve the interaction process by reducing the workload for the user and make the input signal more reliable. Many works [62][60][59] [63] have proved that communication with multiple inputs can improve the quality of human-robot communication. This is due to several reasons.…”

Section: Framework Discussionmentioning

confidence: 99%

A new interaction framework for human and robot

Dinh¹

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First and foremost, I would like to give my special thanks to Professor Seet Gim Lee, Gerald, my supervisor, for your generous support during all these years, for your mentoring, for the experienced guidance, academic supports, patience and valuable advices you have given during my research journey so far, especially for helping me find a way back at the time of being distracted from my research duty. I could not have imagined having a better advisor for my Ph.D study.I want to deeply grateful to Dr. Viatcheslav V Iastrebov for his enthusiastic cooperation and suggestions over the last 4 years when we implemented our project together. My work would have not been possible without your knowledge and experience. Furthermore, you are always a close friend to me and share many funny stories with me during my stay at RRC. I also would like to give big thanks to all my colleagues in Robotics Research Center: Wee Ching, Burhan, Hendra, Choon Yue, William, and Ahmad. You guys are always so nice to me since the first day I came to NTU. I especially wish to thank Ms. Wee Ching for sharing her knowledge and expertise at the beginning phase of my PhD project. I wish to show my great gratitude to my families. Without their unconditional supports and encouragements in moments of difficulties, I would not have been able to accomplish this result. Finally, I would love to specially thank my girlfriend, Ms.

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Multimodal cognitive interface for robot navigation

Cited by 4 publications

References 16 publications

Robot Navigation in Unseen Spaces using an Abstract Map

Robot Navigation in Unseen Spaces using an Abstract Map

A Short Review of Symbol Grounding in Robotic and Intelligent Systems

A new interaction framework for human and robot

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