Multi-modal model predictive control through batch non-holonomic trajectory optimization: Application to highway driving
Standard Model Predictive Control (MPC) or trajectory optimization approaches perform only
a local search to solve a complex non-convex optimization problem. As a result, they cannot …
a local search to solve a complex non-convex optimization problem. As a result, they cannot …
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 …
On the design of control invariant regions for feedback linearized car-like vehicles
This letter proposes a novel procedure to design a control invariant region for feedback-
linearized car-like vehicles subject to linear and steering velocity constraints. To this end …
linearized car-like vehicles subject to linear and steering velocity constraints. To this end …
Learning-based MPC for Autonomous Motion Planning at Freeway Off-ramp Diverging
Off-ramp diverging road segment is the preparation area for vehicles driving away from the
freeway, while it causes more traffic conflicts making it a typical safety bottleneck. Focusing …
freeway, while it causes more traffic conflicts making it a typical safety bottleneck. Focusing …
Flash: Fast and light motion prediction for autonomous driving with Bayesian inverse planning and learned motion profiles
Motion prediction of road users in traffic scenes is critical for autonomous driving systems
that must take safe and robust decisions in complex dynamic environments. We present a …
that must take safe and robust decisions in complex dynamic environments. We present a …
Topology-Driven Parallel Trajectory Optimization in Dynamic Environments
Ground robots navigating in complex, dynamic environments must compute collision-free
trajectories to avoid obstacles safely and efficiently. Nonconvex optimization is a popular …
trajectories to avoid obstacles safely and efficiently. Nonconvex optimization is a popular …
Local Trajectory Planning for Obstacle Avoidance of Unmanned Tracked Vehicles Based on Artificial Potential Field Method
L Zhai, C Liu, X Zhang, C Wang - IEEE Access, 2024 - ieeexplore.ieee.org
A trajectory planning method for local obstacle avoidance based on an improved artificial
potential field (APF) method is proposed, which is aimed at the problem for dual motor …
potential field (APF) method is proposed, which is aimed at the problem for dual motor …
A Set-Theoretic Control Approach to the Trajectory Tracking Problem for Input–Output Linearized Wheeled Mobile Robots
This letter proposes a set-theoretic receding horizon control scheme to address the
trajectory tracking problem for input-constrained differential-drive robots. The proposed …
trajectory tracking problem for input-constrained differential-drive robots. The proposed …
Chance-aware lane change with high-level model predictive control through curriculum reinforcement learning
Lane change in dense traffic typically requires the recognition of an appropriate opportunity
for maneuvers, which remains a challenging problem in self-driving. In this work, we …
for maneuvers, which remains a challenging problem in self-driving. In this work, we …
Proactive Emergency Collision Avoidance for Automated Driving in Highway Scenarios
Uncertainty in the behavior of other traffic participants is a crucial factor in collision
avoidance for automated driving; here, stochastic metrics should often be considered to …
avoidance for automated driving; here, stochastic metrics should often be considered to …