Economic MPC-based planning for marine vehicles: Tuning safety and energy efficiency
Energy efficiency and safety are two critical objectives for marine vehicles operating in environments with obstacles, and they generally conflict with each other. In this paper, we propose a novel online motion planning method of marine vehicles which can make trade-offs between the two design objectives based on the framework of economic model predictive control (EMPC). Firstly, the feasible trajectory with the most safety margin is designed and utilized as tracking reference. Secondly, the EMPC-based receding horizon motion planning algorithm is designed, in which the practical consumed energy and safety measure (i.e., the distance between the planning trajectory and the reference) are considered. Experimental results verify the effectiveness and feasibility of the proposed method.
Code (0)
등록된 구현이 없습니다.
Tasks
Model Predictive ControlMotion PlanningSimilar Papers 제목 키워드 기반
Framework for Robust Motion Planning of Tethered Multi-Robot Systems in Marine Environments
This paper introduces CoralGuide, a novel framework designed for path planning and trajectory optimization for tethered multi-robot systems. We focus on marine robotics, which commonly have tethered configurations of an …
Trajectory PlanningMotion PlanningUncertainty-Aware Active Source Tracking of Marine Pollution using Unmanned Surface Vehicles
This paper proposes an uncertainty-aware marine pollution source tracking framework for unmanned surface vehicles (USVs). By integrating high-fidelity marine pollution dispersion simulation with informative path planning…
Safety-Critical Control of Nonholonomic Vehicles in Dynamic Environments using Velocity Obstacles
This paper considers collision avoidance for vehicles with first-order nonholonomic constraints maintaining nonzero forward speeds, moving within dynamic environments. We leverage the concept of control barrier functions…
Collision AvoidanceLlamarine: Open-source Maritime Industry-specific Large Language Model
Large Language Models (LLMs) have demonstrated substantial potential in addressing complex reasoning tasks, yet their general-purpose nature often limits their effectiveness in specialized domains such as maritime naviga…
Collision AvoidanceDecision MakingLanguage ModelingLanguage Modelling+2Stochastic Model Predictive Control with a Safety Guarantee for Automated Driving: Extended Version
Automated vehicles require efficient and safe planning to maneuver in uncertain environments. Largely this uncertainty is caused by other traffic participants, e.g., surrounding vehicles. Future motion of surrounding veh…
Model Predictive ControlMotion PlanningTrajectory Planning