Category: Brain-Inspired Navigation
3D Spatial Representation: Coding of 3D space by 3D Grid Cells, 3D Border Cells, 3D Head Direction Cells
Latest reports about 3D Spatial Representation by Gily Ginosar at Weizmann Institute of Science and Misun Kim at UCL in the Grid Cell Meeting on May 21-22, 2018. (http://www.cognitive-map.com/img/GCMposters.pdf )
Gily Ginosar, Weizmann Institute of Science
Grid cells recorded …
Navigation in AI-Brain and Bio-Brain
Most animals, including humans, are able to flexible navigate the complex world. They can explore new areas, returning quickly to remembered places, and taking shortcuts. The recent discovery in neuroscience, including place cells, grid cells, head direction cells, border cells, …
How to match panoramas images in opposite viewpoint for visual route recognition?
These references are about key matching methods of panoramas images in forward and backward direction for visual route recognition in brain inspired navigation.
Milford Michael. “Visual route recognition with a handful of bits.” Proc. 2012 Robotics: Science and …
Exciting New Bio-inspired Robots Include Rolling Spider, Flying Fox From Festo
Festo has just announced its two newest bionic learning network robots—one is a very convincing flying fox, and the other is a walking, tumbling robot inspired by a Saharan spider. Over the last few years, we’ve met ants, butterflies, …
How to build robust visual template matching for robot place recognition and navigation?
The following are some references about visual template matching, including theory and demo.
Corke, Peter. Robotics, Vision and Control: Fundamental Algorithms In MATLAB® Second, Completely Revised. Vol. 118. Springer, 2017, pp. 376-392.
Milford, M. and Wyeth, G., 2010. …
How to process panoramic images for scene recognition?
The excerpt note is about panoramic images from Zhang et al., 2007.
Zhang, A. M. (2007). Robust appearance based visual route following in large scale outdoor environments. Proceedings of the Australasian Conference on Robotics and Automation, Brisbane, Australia, 2007.…
How to implement appearance-based scene recognition using panoramic images for persistent navigation and mapping in open areas?
The excerpt note is about vision processing and appearance-based recognition using panoramic images for persistent navigation and mapping in open areas from Michael et al., 2010.
Michael Milford, and Gordon Wyeth. “Persistent Navigation and Mapping using a Biologically Inspired …
How to implement the Loop Closure (Map Correction) in RatSLAM?
This excerpt note is about loop closure (map correction) in RatSLAM from Michael et al., 2008 and Michael 2008 book.
Michael Milford, and Gordon F. Wyeth. “Mapping a Suburb with a Single Camera using a Biologically Inspired SLAM System…
How to represent large areas by reusing cells in 2D continuous attractor network model?
The excerpt note is about how to represent large areas by reusing cells in 2D continuous attractor network model in RatSLAM from Michael et al., 2008, 2010, and Samsonovich et al., 1997, McNaughton et al., 2006.
Michael Milford, and Gordon …
How to represent location based on the place cells？
The excerpt note is about a model of spatial location based on the place cells from the Michael 2008.
Michael Milford. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer-Verlag Berlin Heidelberg Press, …
What is the detail principle of Experience Map: Component, Transition, Creation, Maintenance in RatSLAM?
The excerpt note is about Experience Map: Component, Transition, Creation, Maintenance, from Michael 2008.
Michael Milford. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer-Verlag Berlin Heidelberg Press, pp. 129-143, 149-150, 2008.
I. …
How to build cognitive map (experience map) for autonomous navigation in RatSLAM?
The excerpt note is about how to build Experience Map in RatSLAM from Michael et al 2008.
An experience map is a fine-grained topological map composed of many individual experiences, e, connected by transitions, t. Each experience 
is defined by …
Cognitive Navigation News (2018-003)
1. Can We Copy the Brain?
from the IEEE Spectrum Special Report about AI and Brain Inspired Computing.
From Macro to Micro: A Visual Guide to the Brain
In the Future, Machines Will Borrow …
How to represent robot’s pose with a rate-coded neural network CAN in RatSLAM?
The excerpt note is about robot’s pose representation with a rate-coded neural network, continuous attractor network (CAN) in RatSLAM from Michael and Gordon 2010.
The CAN is a neural network that consists of an array of units with fixed weighted …
How to perform Path Integration in RatSLAM?
The excerpt note is about path integration in RatSLAM from Michael et al. 2010, 2008, 2004.
The RatSLAM system uses poses cells to concurrently represent the beliefs about the location and orientation of the robot. By representing 
in the same …
About
Brain Inspired Navigation Blog
New discovery worth spreading on brain-inspired navigation in neurorobotics and neuroscience
Recent Posts
- How flexible navigation strategies emerge and evolve in freely moving non-human primates?
- How insect integrate spatial and temporal information？
- How the brain coordinates and integrates allocentric, route-centered, and egocentric spatial reference frames at the network level during navigation?
- How spatial coding support auditory conceptual navigation in the entorhinal-hippocampal system?
- How to compose egocentric and allocentric maps for flexible navigation?
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Categories
- 3D Movement
- 3D Navigation
- 3D Path Integration
- 3D Perception
- 3D SLAM
- 3D Spatial Representation
- AI Navigation
- Bio-Inspired Robotics
- Brain-Inspired Navigation
- Cognitive Map
- Cognitive Navigation
- Episodic Memory
- Excerpt Notes
- Flying Vehicle Navigation
- Goal Representation
- Insect Navigation
- Learning to Navigate
- Memory
- Neural Basis of Navigation
- Path Integration
- Path Planning
- Project
- Research Tips
- Robotic Vision
- Self-Flying Vehicles
- Semantic Memory
- Spatial Cognition
- Spatial Cognitive Computing
- Spatial Coordinate System
- Spatial Memory
- Time
- Unclassified
- Visual Cortex
- Visual Cue Cells
Links
- Laboratory of Nachum Ulanovsky
- Jeffery Lab
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- The NeuroBat Lab
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- Laurens Group
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- Moser Group
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- DoellerLab
- MilfordRobotics Group
- The Space and Memory group
- Angelaki Lab
- Spatial Cognition Lab
- McNaughton Lab
- Conradt Group
- The Fiete Lab
- The Cacucci Lab
- The Burak Lab
- Knierim Lab
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- The Dombeck Lab
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- Basu Lab
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- Memory and Navigation Circuits Group
- Neural Circuits and Memory Lab
- The lab of Arseny Finkelstein
- The Epstein Lab
- The Theoretical Neuroscience Lab
- Gu Lab (Spatial Navigation and Memory)
- Fisher Lab (Neural Circuits for Navigation)
- The Alexander Lab (Spatial Cognition and Memory)
- Harvey Lab (Neural Circuits for Navigation)
- Buzsáki Lab
- Brain Computation & Behavior Lab
- ……