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 …
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 …
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 …
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 …
How Self-Motion Updates the Head Direction Cell Attractor?
Laurens J., et al., 2018 reviews head direction cells. They propose a quantitative framework whereby this drive represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction errors of vestibular, visual, and somatosensory cues to improve …
How to implement internal dynamics of the head direction network in brain inspired 1D SLAM?
The excerpt note is from the Michael’s book. The example code is implemented by Fangwen, which can help us to understand the process and principle of the method.
Michael Milford. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning …
About
Brain Inspired Navigation Blog
New discovery worth spreading on brain-inspired navigation in neurorobotics and neuroscience
Recent Posts
- How zebrafish place cells integrate multiple sources of information and flexibly remap to form distinct spatial maps?
- How hippocampal neuronal activity is aligned with action plans?
- How ants use latent learning without map-like representation of space to navigate?
- How shifts in the composition of memory-encoding neuronal ensembles influence the evolution of a memory over time?
- Whether the entorhinal grid system is also involved in predicting where an animal will be in the next moment?
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