Local learning enabled iterative linear quadratic regulator for constrained trajectory planning
Trajectory planning is one of the indispensable and critical components in robotics and
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
Policy iteration based approximate dynamic programming toward autonomous driving in constrained dynamic environment
In the area of autonomous driving, it typically brings great difficulty in solving the motion
planning problem since the vehicle model is nonlinear and the driving scenarios are …
planning problem since the vehicle model is nonlinear and the driving scenarios are …
Decentralized iLQR for cooperative trajectory planning of connected autonomous vehicles via dual consensus ADMM
Cooperative trajectory planning of connected autonomous vehicles (CAVs) generally admits
strong nonlinearity and non-convexity, rendering great difficulties in finding the optimal …
strong nonlinearity and non-convexity, rendering great difficulties in finding the optimal …
Semi-definite relaxation-based ADMM for cooperative planning and control of connected autonomous vehicles
This paper investigates the cooperative planning and control problem for multiple connected
autonomous vehicles (CAVs) in different scenarios. In the existing literature, most of the …
autonomous vehicles (CAVs) in different scenarios. In the existing literature, most of the …
Game-theoretic optimization towards diffeomorphism-based robust control of fuzzy dynamical systems with state and input constraints
This work investigates a game-theoretic optimization approach towards robust control of
uncertain dynamical systems with state and input constraints. The uncertainty involved is …
uncertain dynamical systems with state and input constraints. The uncertainty involved is …
Nonlinear predictive motion control for autonomous mobile robots considering active fault-tolerant control and regenerative braking
To further advance the performance and safety of autonomous mobile robots (AMRs), an
integrated chassis control framework is proposed. In the longitudinal motion control module …
integrated chassis control framework is proposed. In the longitudinal motion control module …
Towards socially responsive autonomous vehicles: A reinforcement learning framework with driving priors and coordination awareness
The advent of autonomous vehicles (AVs) alongside human-driven vehicles (HVs) has
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
Spatiotemporal Receding Horizon Control with Proactive Interaction Towards Autonomous Driving in Dense Traffic
In dense traffic scenarios, ensuring safety while keeping high task performance for
autonomous driving is a critical challenge. To address this problem, this paper proposes a …
autonomous driving is a critical challenge. To address this problem, this paper proposes a …
ADMM-based parallel optimization for multi-agent collision-free model predictive control
Z Cheng, J Ma, X Zhang, CW de Silva… - arXiv preprint arXiv …, 2021 - arxiv.org
This paper investigates the multi-agent collision-free control problem for medium and large
scale systems. For such multi-agent systems, it is the typical situation where conventional …
scale systems. For such multi-agent systems, it is the typical situation where conventional …
Optimizing trajectories with closed-loop dynamic SQP
Indirect trajectory optimization methods such as Differential Dynamic Programming (DDP)
have found considerable success when only planning under dynamic feasibility constraints …
have found considerable success when only planning under dynamic feasibility constraints …