This article presents a novel method for exactly reformulating nondifferentiable collision
avoidance constraints into smooth, differentiable constraints using strong duality of convex …

This paper is focused on planning fast, accurate, and optimal trajectories for autonomous
parking. Nominally, this task should be described as an optimal control problem (OCP) …

With the aims of safe, smart and sustainable future mobility, a personalized approach of
trajectory planning and control based on user preferences is developed for lane-change of …

Trajectory planning for a heavy-duty mining truck near the loading/dumping sites of an open-
pit mine is difficult. As opposed to trajectory planning for a small-sized passenger car in a …

Trajectory planning for automated parking has been widely known as more challenging than
that for on-road driving due to the nonconvex kinematics, high-dimensional collision …

In this article, a novel approach of decision-making and motion control is designed for
realizing safe and personalized driving of autonomous vehicles. A new lane-change …

Obstacle avoidance between polytopes is a chal-lenging topic for optimal control and
optimization-based tra-jectory planning problems. Existing work either solves this problem …

Path planning algorithms are crucial components in the process of smart parking. At present,
there are many path planning algorithms designed for smart parking. A well-designed path …

Maneuvering a general 2‐trailer with a car‐like tractor in backward motion is a task that
requires a significant skill to master and is unarguably one of the most complicated tasks a …

In this article, we propose a novel framework for approximating the MPC policy for linear
parameter-varying systems using supervised learning. Our learning scheme guarantees …