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Recent advances in path integral control for trajectory optimization: An overview in theoretical and algorithmic perspectives
This paper presents a tutorial overview of path integral (PI) approaches for stochastic
optimal control and trajectory optimization. We concisely summarize the theoretical …
optimal control and trajectory optimization. We concisely summarize the theoretical …
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 …
[HTML][HTML] A Survey of Autonomous Vehicle Behaviors: Trajectory Planning Algorithms, Sensed Collision Risks, and User Expectations
Autonomous vehicles are rapidly advancing and have the potential to revolutionize
transportation in the future. This paper primarily focuses on vehicle motion trajectory …
transportation in the future. This paper primarily focuses on vehicle motion trajectory …
Distributed differential dynamic programming architectures for large-scale multiagent control
This article proposes two decentralized multiagent optimal control methods that combine the
computational efficiency and scalability of differential dynamic programming (DDP) and the …
computational efficiency and scalability of differential dynamic programming (DDP) and the …
A cost-effective cooperative exploration and inspection strategy for heterogeneous aerial system
In this paper, we propose a cost-effective strategy for heterogeneous UAV swarm systems
for cooperative aerial inspection. Unlike previous works, the proposed method does not rely …
for cooperative aerial inspection. Unlike previous works, the proposed method does not rely …
NVP-HRI: Zero shot natural voice and posture-based human–robot interaction via large language model
Abstract Effective Human–Robot Interaction (HRI) is crucial for future service robots in aging
societies. Existing solutions are biased towards only well-trained objects, creating a gap …
societies. Existing solutions are biased towards only well-trained objects, creating a gap …
Flexible final-time stochastic differential dynamic programming for autonomous vehicle trajectory optimization
In this article, the problem of autonomous vehicle trajectory optimization with flexible final
time is concerned under the consideration of stochastic disturbances. Stochastic differential …
time is concerned under the consideration of stochastic disturbances. Stochastic differential …
Global Multi-Phase Path Planning Through High-Level Reinforcement Learning
In this paper, we introduce the Global Multi-Phase Path Planning () algorithm in planner
problems, which computes fast and feasible trajectories in environments with obstacles …
problems, which computes fast and feasible trajectories in environments with obstacles …
[فهرست منابع][C] Action Correction-Enhanced Multi-Agent Reinforcement Learning for Path Planning in Urban Environments
H Pan, L Han, J Yan, R Liu - Unmanned Systems, 2025 - World Scientific
In urban environments, the path planning of unmanned aerial vehicles (UAVs) presents
significant challenges, particularly since they are tasked with executing various operations in …
significant challenges, particularly since they are tasked with executing various operations in …