Leo Clement, Sebastian Schwarz, Antoine Wystrach. Latent learning without map-like representation of space in navigating ants. bioRxiv 2024.08.29.610243; doi: https://doi.org/10.1101/2024.08.29.610243
Abstract
“Desert ants are excellent navigators. Each individual learns long foraging routes meandering between the trees and bushes in …
Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra. Emergence of Maps in the Memories of Blind Navigation Agents. arXiv:2301.13261 [cs.AI], 2023.
Abstact
“Animal navigation research posits that organisms build and maintain internal spatial representations, …
Ben Sorscher, Gabriel C Mel, Aran Nayebi, Lisa Giocomo, Daniel Yamins, Surya Ganguli. When and why grid cells appear or not in trained path integrators. bioRxiv 2022.11.14.516537; doi: https://doi.org/10.1101/2022.11.14.516537
Abstract
“Recent work has claimed that the emergence of grid …
Zhu H, Liu H, Ataei A, Munk Y, Daniel T, Paschalidis IC (2020) Learning from animals: How to Navigate Complex Terrains. PLoS Comput Biol 16(1): e1007452. https://doi.org/10.1371/journal.pcbi.1007452
Abstract
“We develop a method to learn a bio-inspired motion control …
Gao, Ruiqi & Xie, Jianwen & Zhu, Song & Wu, Yingnian. Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion. ICLR 2019
Abstract
“This paper proposes a representational model for grid cells. In …
Robin Grob, Pauline N. Fleischmann and Wolfgang Rössler*. Learning to navigate – how desert ants calibrate their compass systems. Neuroforum 2019. https://doi.org/10.1515/nf-2018-0011
Navigating through the environment is a challenging task that animals cope with on a daily basis. Many …
MURI Project Title: “Neuro-Autonomy: Neuroscience-Inspired Perception, Navigation, and Spatial Awareness for Autonomous Robots”
Project Website: http://sites.bu.edu/neuroautonomy/
https://electrical.eng.unimelb.edu.au/control-signal-processing/neuro-autonomy
The following content is extracted from the http://www.bu.edu.
A Boston University-led research team was selected to receive a $7.5 million Multidisciplinary …
NeuroSLAM: Neural Simultaneous Localization and Mapping Workshop
Simultaneous Localization and Mapping (or SLAM) refers to the problem of constructing a map of an unknown environment as it is actively being explored. SLAM has been treated extensively in mobile robotics, providing …
Robots have walked on legs for decades. Today’s most advanced humanoid robots can tramp along flat and inclined surfaces, climb up and down stairs, and slog through rough terrain. Some can even jump.
A report about legged robots on the …
A latest report about grid cells from Sainsbury Wellcome Centre at UCL. The following is excerpted from the report.
Our ability to navigate the world, and form episodic memories, relies on an accurate representation of the environment around us. …
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 …
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. …
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, …
Brain Inspired Navigation Blog
New discovery worth spreading on brain-inspired navigation in neurorobotics and neuroscience