The aim of this paper is to present a local trajectory planning method based on nonlinear
optimization that is able to generate a dynamically feasible, comfortable and customizable …

In this paper, an efficient real-time autonomous driving motion planner with trajectory
optimization is proposed. The planner first discretizes the plan space and searches for the …

This paper presents a novel local motion planning framework in a hierarchical manner for
autonomous vehicles to follow a trajectory and agilely avoid obstacles. In the upper layer, a …

In this paper, we consider the problem of unmanned aerial vehicle (UAV) path planning. The
traditional path planning algorithm has the problems of low efficiency and poor adaptability …

Predictive motion planning is the key to achieve energy-efficient driving, which is one of the
main benefits of automated driving. Researchers have been studying the planning of …

Model predictive control (MFC) approach is prone to loss of feasibility due to the limited
prediction horizon for decision making. For autonomous vehicle motion planning, many of …

This paper presents a framework for fast and robust motion planning designed to facilitate
automated driving. The framework allows for real-time computation even for horizons of …

Efficient trajectory planning of autonomous vehicles in complex traffic scenarios is of interest
both academically and in automotive industry. Time efficiency and safety are of key …

We propose an online planning approach for racing that generates the time-optimal
trajectory for the upcoming track section. The resulting trajectory takes the current vehicle …

Trajectory planning using Mixed Integer Linear Programming (MILP) is a powerful approach
because vehicle dynamics and other constraints can be taken into account. However, it is …