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A bio-inspired visual collision detection network integrated with dynamic temporal variance feedback regulated by scalable functional countering jitter streaming.

Neural networks : the official journal of the International Neural Network Society
In pursuing artificial intelligence for efficient collision avoidance in robots, researchers draw inspiration from the locust's visual looming-sensitive neural circuit to establish an efficient neural network for collision detection. However, existin...

Barrier-critic-disturbance approximate optimal control of nonzero-sum differential games for modular robot manipulators.

Neural networks : the official journal of the International Neural Network Society
In this paper, for addressing the safe control problem of modular robot manipulators (MRMs) system with uncertain disturbances, an approximate optimal control scheme of nonzero-sum (NZS) differential games is proposed based on the control barrier fun...

Tracking control problem of nonlinear strict-feedback systems with input nonlinearity: An adaptive neural network dynamic surface control method.

PloS one
In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To ...

FusionOC: Research on optimal control method for infrared and visible light image fusion.

Neural networks : the official journal of the International Neural Network Society
Infrared and visible light image fusion can solve the limitations of single-type visual sensors and can boost the target detection performance. However, since the traditional fusion strategy lacks the controllability and feedback mechanism, the fusio...

Distributed leader-following bipartite consensus for one-sided Lipschitz multi-agent systems via dual-terminal event-triggered mechanism.

Neural networks : the official journal of the International Neural Network Society
This article analyses leader-following bipartite consensus for one-sided Lipschitz multi-agent systems by dual-terminal event-triggered output feedback control approach. A distributed observer is designed to estimate unknown system states by employin...

Tipping prediction of a class of large-scale radial-ring neural networks.

Neural networks : the official journal of the International Neural Network Society
Understanding the emergence and evolution of collective dynamics in large-scale neural networks remains a complex challenge. This paper seeks to address this gap by applying dynamical systems theory, with a particular focus on tipping mechanisms. Fir...

Larger and more instructable language models become less reliable.

Nature
The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational resources) and bespoke shaping up (including post-filtering, fine ...

MRI-compatible and sensorless haptic feedback for cable-driven medical robotics to perform teleoperated needle-based interventions.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical robotics have demonstrated their significance in assisting physicians during minimally invasive surgery. Especially, the integration of haptic and tactile feedback technologies can enhance the surgeon's performance and overall patie...

Aperiodically intermittent quantized control-based exponential synchronization of quaternion-valued inertial neural networks.

Neural networks : the official journal of the International Neural Network Society
Inertial neural networks are proposed via introducing an inertia term into the Hopfield models, which make their dynamic behavior more complex compared to the traditional first-order models. Besides, the aperiodically intermittent quantized control o...

A new hybrid learning control system for robots based on spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents a new hybrid learning and control method that can tune their parameters based on reinforcement learning. In the new proposed method, nonlinear controllers are considered multi-input multi-output functions and then the functions ar...