Brain Inspired Navigation Blog

Category: Cognitive Navigation

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…

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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 …

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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, …

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What is the future of grand challenges for robot navigation and exploration in extreme environments?

The excerpt note is about the grand challenges of robot navigation and exploration in extreme environments in the next 5 to 10 years according to the latest paper published in Science Robotics (Yang et al., Sci Robotics 2018).

Yang, G.Z., …

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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. …

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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 …

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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

Why We Should Copy the Brain

In the Future, Machines Will Borrow …

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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 …

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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 …

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How does the velocity take effects on movement of activity of Pose Cells in RatSLAM?

The excerpt note is about how to move the activity of pose cells according to the translational and rotational velocity in RatSLAM from Michael et al. 2008, 2004.

The new path integration method shifts existing pose cell activity rather than …

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How to update the activity of pose cells in RatSLAM?

The excerpt note is from Michael et al., 2008, which explains the detail process to update the activity of pose cells in RatSLAM.

Milford, Michael J., and Gordon F. Wyeth. “Mapping a suburb with a single camera using a …

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How to build robust, visual-inertial state estimation for autonomous navigation?

Robust, Visual-Inertial State Estimation: from Frame-based to Event-based Cameras

This lecture was presented by Professor Davide Scaramuzza at Affiliation University of Zurich, ETH Zurich in September 25, 2017 on Series Microsoft Research Talks.

Professor Davide Scaramuzza presented main algorithms to …

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Why drones can learn to navigate autonomously by imitating cars and bicycles?

Drones learn to navigate autonomously by imitating cars and bicycles powered by AI

January 23, 2018, by University of Zurich

Developed by UZH researchers, the algorithm DroNet allows drones to fly completely by themselves through the streets of a city …

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How to enable robot cognitive mapping inspired by Grid Cells, Head Direction Cells and Speed Cells？

Taiping Zeng, and Bailu Si. “Cognitive Mapping Based on Conjunctive Representations of Space and Movement.” Frontiers in Neurorobotics 11 (2017).

In this work, the researchers developed a cognitive mapping model for mobile robots, taking advantage of the coding …

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How to perform robot place recognition with multi-scale, multi-sensor system inspired by place cells?

Adam Jacobson, Zetao Chen, Michael Milford. Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework. Biological Cybernetics, Jan 20, 2018, https://doi.org/10.1007/s00422-017-0745-7 .

This paper presented a biologically inspired multi-scale, multi-sensor place recognition system that incorporates the …

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