BACKGROUND: A number of space activities (e.g., extravehicular astronaut rescue, cooperation in satellite services, space station supplies, and assembly) are implemented directly or assisted by remote robotic arms. Our study aimed to reveal those ind...
Neural networks : the official journal of the International Neural Network Society
28064015
Electrophysiological studies in animals may provide a great insight into developing brain-like models of spatial cognition for robots. These studies suggest that the spatial ability of animals requires proper functioning of the hippocampus and the en...
IEEE/ACM transactions on computational biology and bioinformatics
28182546
Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel...
IEEE transactions on neural networks and learning systems
28436902
The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in ...
For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requ...
We first tested the effect of differing tactile informational forms (i.e. directional cues vs. static cues vs. dynamic cues) on objective performance and perceived workload in a collaborative human-robot task. A second experiment evaluated the influe...
The aim of this study is to derive a guidance law by which an unmanned aerial system(s) (UAS) can pursue a moving target at a constant distance, while concealing its own motion. We derive a closed-form solution for the trajectory of the UAS by imposi...
BACKGROUND: Understanding the neural substrate of information encoding and processing requires a precise control of the animal's behavior. Most of what has been learned from the rodent navigational system results from relatively simple tasks in which...
Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and...
Spatial cells in the hippocampal complex play a pivotal role in the navigation of an animal. Exact neural principles behind these spatial cell responses have not been completely unraveled yet. Here we present two models for spatial cells, namely the ...