As shown by recent studies, machine intelligence-enabled systems are vulnerable to test
cases resulting from either adversarial manipulation or natural distribution shifts. This has …

Reinforcement learning (RL) can learn from past failures and has the potential to provide
self-improvement ability and higher-level intelligence. However, the current RL algorithms …

The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

To achieve accuracy and stable speed tracking under different conditions, a speed tracking
method for the unmanned driving robot vehicle with sliding mode gains adjusted by a fuzzy …

In order to improve the shift precision of the gearshift manipulator, a coordinated control
method for the gearshift manipulator based on the Deep Deterministic Policy Gradient …

The clearance joint is very important to the nonlinear dynamic characteristics of mechanism.
This paper presents a nonlinear dynamic characteristic modeling method of shift …

With the widespread use of robots in the world, including rescue operations and special
surgeries, the precise design of robots is of particular importance. The shift manipulator is a …

When talking about automation,“autonomous vehicles”, often abbreviated as AVs, come to
mind. In transitioning from the “driver” mode to the different automation levels, there is an …

To realise the accurate and stable longitudinal control of the vehicle manipulated by the
driving robot (DRV) under different test conditions, a longitudinal robust dynamic …

In this article, a neural active disturbance rejection adaptive lateral manipulation control
method for an unmanned driving robot (UDR) is proposed to realize accurate and stable …