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To efficiently deploy robotic systems in society, mobile robots must move autonomously and safely through complex environments. Nonlinear model predictive control (MPC) methods provide a natural way to find a dynamically feasible trajectory…

This paper presents a novel learning-based trajectory planning framework for quadrotors that combines model-based optimization techniques with deep learning. Specifically, we formulate the trajectory optimization problem as a quadratic…

Robotics · Computer Science 2023-12-05 Yuwei Wu , Xiatao Sun , Igor Spasojevic , Vijay Kumar

The increasing popularity of quadrotors has given rise to a class of predominantly vision-driven vehicles. This paper addresses the problem of perception-aware time optimal path parametrization for quadrotors. Although many different…

Robotics · Computer Science 2020-05-29 Igor Spasojevic , Varun Murali , Sertac Karaman

This paper develops computationally efficient data-driven model predictive control (MPC) for Agile quadrotor flight. Agile quadrotors in high-speed flights can experience high levels of aerodynamic effects. Modeling these turbulent…

Robotics · Computer Science 2023-05-30 Wonoo Choo , Erkan Kayacan

In this paper, we investigate a secure communication architecture based on unmanned aerial vehicle (UAV), which enhances the security performance of the communication system through UAV trajectory optimization. We formulate a control…

Signal Processing · Electrical Eng. & Systems 2024-11-08 Zhendong Li , Chang Su , Zhou Su , Haixia Peng , Yuntao Wang , Wen Chen , Qingqing Wu

We consider the problem of generating a time-optimal quadrotor trajectory that attains a set of prescribed waypoints. This problem is challenging since the optimal trajectory is located on the boundary of the set of dynamically feasible…

Robotics · Computer Science 2020-06-05 Gilhyun Ryou , Ezra Tal , Sertac Karaman

In this paper, we present a novel strategy to compute minimum-time trajectories for quadrotors in constrained environments. In particular, we consider the motion in a given flying region with obstacles and take into account the physical…

Optimization and Control · Mathematics 2017-06-22 Sara Spedicato , Giuseppe Notarstefano

The Model Predictive Control (MPC) trajectory tracking problem of an unmanned quadrotor with input and output constraints is addressed. In this article, the dynamic models of the quadrotor are obtained purely from operational data in the…

Systems and Control · Computer Science 2017-07-17 Gang Cao , Edmund M-K Lai , Fakhrul Alam

Nonlinear Model Predictive Control (NMPC) is a powerful approach for controlling highly dynamic robotic systems, as it accounts for system dynamics and optimizes control inputs at each step. However, its high computational complexity makes…

Robotics · Computer Science 2026-02-27 Van Chung Nguyen , Pratik Walunj , Chuong Le , An Duy Nguyen , Hung Manh La

This paper investigates optimal takeoff trajectory planning for a quadrotor modeled with vertical-plane rigid body dynamics in an uncertain, one-dimensional wind-field. The wind-field varies horizontally and propagates across an operating…

Systems and Control · Electrical Eng. & Systems 2024-02-05 Nicholas Kakavitsas , Artur Wolek

This letter presents a new predictive control architecture for high-dimensional robotic systems. As opposed to a conventional Model Predictive Control (MPC) approach to locomotion that formulates a hierarchical sequence of optimization…

Robotics · Computer Science 2021-05-13 He Li , Robert J. Frei , Patrick M. Wensing

This paper presents a trajectory planning method for articulated commercial vehicles, specifically tractor-semitrailers, based on Model Predictive Contouring Control (MPCC). Although MPCC has proven effective for passenger cars, it is…

In this paper, we present a motion planning strategy for UAVs that generates a time-optimal trajectory to survey a given target area. There are several situations where completing an aerial survey is time sensitive, such as gaining…

Robotics · Computer Science 2022-03-08 Tankasala Srinath , Pehlivanturk Can , Pryor Mitch

In this paper we present a model predictive control (MPC) approach to optimize vehicle scheduling and routing in an autonomous mobility-on-demand (AMoD) system. In AMoD systems, robotic, self-driving vehicles transport customers within an…

Systems and Control · Computer Science 2017-08-15 Rick Zhang , Federico Rossi , Marco Pavone

Trajectory planning and control have historically been separated into two modules in automated driving stacks. Trajectory planning focuses on higher-level tasks like avoiding obstacles and staying on the road surface, whereas the controller…

Robotics · Computer Science 2022-09-21 Rowan Dempster , Mohammad Al-Sharman , Derek Rayside , William Melek

Formation flight is when multiple objects fly together in a coordination. Various automatic control methods have been used for the autonomous execution of formation flight of aerial vehicles. In this paper, the capacity of the model…

Robotics · Computer Science 2023-12-05 Harun Celik , Dilara Kilinc

This paper presents a Model Predictive Control (MPC) scheme for flight scheduling and energy management of electric aviation networks, where electric aircraft transport passengers between electrified airports equipped with sustainable…

Systems and Control · Electrical Eng. & Systems 2025-11-18 Finn Vehlhaber , Mauro Salazar

One of the keys to flying quadrotors is to optimize their trajectories within the set of collision-free corridors. These corridors impose nonconvex constraints on the trajectories, making real-time trajectory optimization challenging. We…

Optimization and Control · Mathematics 2022-08-16 Yue Yu , Kartik Nagpal , Skye Mceowen , Behçet Açıkmeşe , Ufuk Topcu

Precise positioning and fast traversal times are crucial in achieving high productivity and scale in machining. This paper compares two optimization-based predictive control approaches that achieve high performance. In the first approach,…

Systems and Control · Electrical Eng. & Systems 2020-09-22 Alexander Liniger , Luca Varano , Alisa Rupenyan , John Lygeros

This paper presents a novel method for controlling teams of unmanned aerial vehicles using Stochastic Optimal Control (SOC) theory. The approach consists of a centralized high-level planner that computes optimal state trajectories as…

Systems and Control · Electrical Eng. & Systems 2020-05-14 Vicenç Gómez , Sep Thijssen , Andrew Symington , Stephen Hailes , Hilbert J. Kappen