In this paper, we present an innovative risk-bounded motion planning methodology for
stochastic multi-agent systems. For this methodology, the disturbance, noise, and model …

The UAV flight control tasks, especially their stabilities under large disturbances, are always
complex and troublesome. In many application environments, drones are subject to both …

Accurate and fast motion prediction such as pedestrian motion prediction (PMP) is crucial for
safe autonomous driving. Much research effort has been devoted to studying the reactive …

Parallel robot systems have become increasingly applied due to significant advantages
such as fast operating speed and high accuracy. Researchers are currently focusing on …

This paper proposes a Dynamic Collision-Free Cooperative decision-making method based
on the Predicted InterDistance Profile (DCFC-PIDP) for Connected Autonomous Vehicles …

This book details cutting-edge research into human-like driving technology, utilising game
theory to better suit a human and machine hybrid driving environment. Covering feature …

In many specific scenarios, accurate and effective system identification is a commonly
encountered challenge in the model predictive control (MPC) formulation. As a …

Quadrotors with the ability to perch on moving inclined surfaces can save energy and extend
their travel distance by leveraging ground vehicles. Achieving dynamic perching places high …

For a specific class of under-actuated mechanical systems, non-holonomic servo constraints
and model uncertainties are usually encountered. For such systems, this paper investigates …

This thesis addresses the critical challenge of ensuring safety in autonomous exploration
within unknown, unstructured, dynamic environments, a domain filled with various types of …