Gateway identity and spatial remapping in a combined grid and place cell attractor

Baumann, T.; Mallot, Hanspeter A.

doi:10.1016/j.neunet.2022.10.019

Cited by 5 publications

(2 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For this kind of robot, all actions are completed by one or more mechanical arms, rather than arbitrarily changing the arm position and motion trajectory. Figure 1 is the joint position control diagram of the mechanical arm [10][11].…”

Section: Manipulator Control Of Construction Machinerymentioning

confidence: 99%

Optimization of Control Method of Construction Machinery Manipulator Based on Neural Network

2023

KME

View full text Add to dashboard Cite

Neural network is one of the important basic knowledge in computer, chemistry and information science, microelectronics technology and other fields. It has good universality in dealing with nonlinear system problems, and is widely used in industrial automation and intelligent control. This paper mainly introduces the mathematical model, algorithm design and implementation method of the construction machinery robot arm, and studies and analyzes its kinematics. Based on the neural network and artificial neuron theory, this paper constructs the robot arm position recognition technology in the object feature database for the characteristics and requirements of the subject. Finally, the function of the robot arm control model is tested, and the test results show that the arm support of the model has a long elongation distance, which can meet the production requirements.

show abstract

Section: Manipulator Control Of Construction Machinerymentioning

confidence: 99%

Optimization of Control Method of Construction Machinery Manipulator Based on Neural Network

2023

KME

View full text Add to dashboard Cite

show abstract

“…In our simulation, we placed vertices at all corners of the maze, but other choices are possible. A neural network model assuming metric representations within small regions and categorical knowledge of these regions themselves has been presented by Baumann and Mallot (2023) [49].…”

Section: Plos Computational Biologymentioning

confidence: 99%

Metric information in cognitive maps: Euclidean embedding of non-Euclidean environments

Baumann,

Mallot

2023

PLoS Comput Biol

Self Cite

View full text Add to dashboard Cite

The structure of the internal representation of surrounding space, the so-called cognitive map, has long been debated. A Euclidean metric map is the most straight-forward hypothesis, but human navigation has been shown to systematically deviate from the Euclidean ground truth. Vector navigation based on non-metric models can better explain the observed behavior, but also discards useful geometric properties such as fast shortcut estimation and cue integration. Here, we propose another alternative, a Euclidean metric map that is systematically distorted to account for the observed behavior. The map is found by embedding the non-metric model, a labeled graph, into 2D Euclidean coordinates. We compared these two models using data from a human behavioral study where participants had to learn and navigate a non-Euclidean maze (i.e., with wormholes) and perform direct shortcuts between different locations. Even though the Euclidean embedding cannot correctly represent the non-Euclidean environment, both models predicted the data equally well. We argue that the embedding naturally arises from integrating the local position information into a metric framework, which makes the model more powerful and robust than the non-metric alternative. It may therefore be a better model for the human cognitive map.

show abstract

Artificial Neural Networks with Interacting Output Units

Mallot

2024

Computational Neuroscience

View full text Add to dashboard Cite

Gateway identity and spatial remapping in a combined grid and place cell attractor

Cited by 5 publications

References 82 publications

Optimization of Control Method of Construction Machinery Manipulator Based on Neural Network

Optimization of Control Method of Construction Machinery Manipulator Based on Neural Network

Metric information in cognitive maps: Euclidean embedding of non-Euclidean environments

Artificial Neural Networks with Interacting Output Units

Contact Info

Product

Resources

About