Category: Brain-Inspired Navigation

What if we could design an autonomous flying robot with the navigational and learning abilities of a honeybee?

Some brief introduction about  the project ‘Brains on Board: Neuromorphic Control of Flying Robots’  

What if we could design an autonomous flying robot with the navigational and learning abilities of a honeybee? Such a computationally and energy-efficient autonomous …

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How the brain makes a map of space?

A brief review on the neural cells of navigation in the brain by Professor Kate Jeffery.

Please read the slide at https://www.cambridgeconference.com/wp-content/uploads/2017/08/0955-presentation-kate-Jeffery.pdf 

Some snapshot from the report. The neural cells include place cells, head direction cells, grid cells, etc.…

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Brain-inspired dynamic path replanning in autonomous navigation for robotic swarms

What do animal brains have in common with a swarm of robots? 

In an effort to improve robotic swarming algorithms, an interdisciplinary team of scientists will study how the brain allows an animal to navigate and change its route while …

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Animals Teach Robots to Find Their Way

By Chris Edwards
Communications of the ACM, August 2018, Vol. 61 No. 8, Pages 14-16. 10.1145/3231168

Mammalian research has underpinned the key models used in robot development. Analogs of neural networks found in the rat’s brain underpin the most widespread

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How landmark and self-motion cues combine during navigation to generate spatial representations?

The excerpt note is about how combine landmark and self-motion cues for navigation from Campbell et al., 2018.

Campbell, Malcolm G., Samuel A. Ocko, Caitlin S. Mallory, Isabel I. C. Low, Surya Ganguli & Lisa M. Giocomo. Principles governing the

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How do bats navigate in 3D environments?

The excerpt note is about bat navigation from Yovel & Ulanvosky 2017.

Yovel, Yossi, and Nachum Ulanvosky. “1.18 Bat Navigation.” Learning and Memory: A Comprehensive Reference (2017): 333.

Navigation, the capacity to plan and execute a goal-directed path,

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Biologically inspired visual odometry based on the computational model of grid cells

A biologically inspired visual odometry based on the computational model of grid cells, which is developed based on the the source code of the computational model of grid cells: http://clm.utexas.edu/fietelab/code.htm, and LIBVISO2: http://www.cvlibs.net/software/libviso/, by Huimin Lu, Junhao Xiao, …

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How to unlock the secrets of 3D navigation in the brain?

A Nature  News Feature report the research story of 3D navigation in  Nachum Ulanovsky lab. Titled “100 bats and a long, dark tunnel: one neuroscientist’s quest to unlock the secrets of 3D navigation” published in Nature News at …

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Path Integration in a Continuous Attractor Network Model

The excerpt note is about path integration with continuous attractor network according to McNaughton B. L., et al., 2006.

McNaughton, Bruce L., Francesco P. Battaglia, Ole Jensen, Edvard I. Moser, and May-Britt Moser. “Path integration and the neural basis

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Why is it a so difficult problem for navigating in a three-dimensional world?

The excerpt note is about spatial cognition in non-horizontal environments by Jeffery K. J. et al., 2013.

Jeffery, Kathryn J., Aleksandar Jovalekic, Madeleine Verriotis, and Robin Hayman. “Navigating in a three-dimensional world.” Behavioral and Brain Sciences 36, no. …

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Learning to Navigate

The excerpt note is about the novel approach of learning to navigate proposed by DeepMind research team in past few period of time.

How did you learn to navigate the neighborhood of your childhood, to go to a friend’s house, …

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How to build spatial representation model (x, y, z, yaw) for 3D SLAM inspired by the brain?

The excerpt note is some relevant references about 2.5D SLAM inspired by the brain, which is expanded from the RatSLAM system.

Guth F. A. et. al. present an Hippo 3D (DolphinSLAM), expanded from the RatSLAM system, which was initially designed …

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3D SLAM: the grand challenge and ultimate goal for robotic perception.

Real-world applications in GPS-denied environments require robust mapping and perception techniques to enable mobile systems to autonomously navigate complex 3D environments.

Robotic environments are in general 3D, involving translation in three directions, x, y, and z, and rotation around three …

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iNav 2018: How does the brain know where it is, where it is going, and how to get from one place to another?

The 2nd Interdisciplinary Navigation Symposium (iNav 2018) was held in June 2018 in Québec, Canada, organized by Jeffery Taube, Thomas Wolbers, Kate Jeffery, Laure Rondi-Reig, David Dickman, Mayank Mehta. The meeting aims to bring together a diverse group of scientists …

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Long-distance Navigation and magnetoreception in migratory animals

The excerpt note is about twenty important mechanistic questions related to long-distance animal navigation from Mouritsen, H. (2018).

Mouritsen, H. (2018). Long-distance navigation and magnetoreception in migratory animals. Nature, 558(7708), 50.

Abstract: For centuries, humans have been fascinated by

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