UAV trajectory planning with probabilistic geo-fence via iterative chance-constrained optimization
Chance-constrained optimization provides a promi-sing framework for solving control and
planning problems with uncertainties, due to its modeling capability to capture randomness …
planning problems with uncertainties, due to its modeling capability to capture randomness …
Pilot: Efficient planning by imitation learning and optimisation for safe autonomous driving
Achieving a proper balance between planning quality, safety and efficiency is a major
challenge for autonomous driving. Optimisation-based motion planners are capable of …
challenge for autonomous driving. Optimisation-based motion planners are capable of …
Risk-aware optimal control for automated overtaking with safety guarantees
This article proposes a solution to the overtaking control problem where an automated
vehicle tries to overtake another vehicle with uncertain motion. Our solution allows the …
vehicle tries to overtake another vehicle with uncertain motion. Our solution allows the …
Learning from experience for rapid generation of local car maneuvers
Being able to rapidly respond to the changing scenes and traffic situations by generating
feasible local paths is of pivotal importance for car autonomy. We propose to train a deep …
feasible local paths is of pivotal importance for car autonomy. We propose to train a deep …
A simplified vehicle dynamics model for motion planner designed by nonlinear model predictive control
F Gao, Q Hu, J Ma, X Han - Applied Sciences, 2021 - mdpi.com
Motion planning by considering it as an optimal problem is an effective and widely
applicable method. Its comprehensive performance greatly depends on the vehicle …
applicable method. Its comprehensive performance greatly depends on the vehicle …
Functional model of a Self-driving car control system
K Sviatov, N Yarushkina, D Kanin, I Rubtcov, R Jitkov… - Technologies, 2021 - mdpi.com
The article describes a structural and functional model of a self-driving car control system,
which generates a wide class of mathematical problems. Currently, control systems for self …
which generates a wide class of mathematical problems. Currently, control systems for self …
Linear-quadratic optimal control in maximal coordinates
J Brüdigam, Z Manchester - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The linear-quadratic regulator (LQR) is an efficient control method for linear and linearized
systems. Typically, LQR is implemented in minimal coordinates (also called generalized or" …
systems. Typically, LQR is implemented in minimal coordinates (also called generalized or" …
DDK: A deep Koopman approach for dynamics modeling and trajectory tracking of autonomous vehicles
Y Xiao - arXiv preprint arXiv:2110.14700, 2021 - arxiv.org
Autonomous driving has attracted lots of attention in recent years. An accurate vehicle
dynamics is important for autonomous driving techniques, eg trajectory prediction, motion …
dynamics is important for autonomous driving techniques, eg trajectory prediction, motion …
Towards learning generalizable driving policies from restricted latent representations
Training intelligent agents that can drive autonomously in various urban and highway
scenarios has been a hot topic in the robotics society within the last decades. However, the …
scenarios has been a hot topic in the robotics society within the last decades. However, the …
Weighted linearization of nonlinear systems
D Rotondo - IEEE Transactions on Circuits and Systems II …, 2021 - ieeexplore.ieee.org
This brief proposes a generalization of the linearization technique in which the computation
of the Jacobian matrices at the state trajectory of interest is replaced by the multiple integral …
of the Jacobian matrices at the state trajectory of interest is replaced by the multiple integral …