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Robust feedback motion planning via contraction theory

INTERNATIONAL JOURNAL OF robotics RESEARCH 2023年第9期42卷 655-688页

作者： Singh, Sumeet Landry, Benoit Majumdar, Anirudha Slotine, Jean-Jacques Pavone, Marco Stanford Univ Dept Aeronaut & Astronaut 496 Lomita Mall Stanford CA 94305 USA Princeton Univ Dept Mech & Aerosp Engn Princeton NJ USA MIT Dept Mech Engn Cambridge MA USA

We present a framework for online generation of robust motion plans for robotic systems with nonlinear dynamics subject to bounded disturbances, control constraints, and online state constraints such as obstacles. In an offline phase, one computes the structure of a feedback controller that can be efficiently implemented online to track any feasible nominal trajectory. The offline phase leverages contraction theory, specifically, Control Contraction Metrics, and convex optimization to characterize a fixed-size "tube" that the state is guaranteed to remain within while tracking a nominal trajectory (representing the center of the tube). In the online phase, when the robot is faced with obstacles, a motion planner uses such a tube as a robustness margin for collision checking, yielding nominal trajectories that can be safely executed, that is, tracked without collisions under disturbances. In contrast to recent work on robust online planning using funnel libraries, our approach is not restricted to a fixed library of maneuvers computed offline and is thus particularly well-suited to applications such as UAV flight in densely cluttered environments where complex maneuvers may be required to reach a goal. We demonstrate our approach through numerical simulations of planar and 3D quadrotors, and hardware results on a quadrotor platform navigating a complex obstacle environment while subject to aerodynamic disturbances. The results demonstrate the ability of our approach to jointly balance motion safety and efficiency for agile robotic systems.

关键词： aerial robotics cognitive control architectures cognitive robotics field and service robotics mechanisms design, and control motion control underactuated robots

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RotorTM: A Flexible Simulator for aerial Transportation and Manipulation

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IEEE TRANSACTIONS ON robotics 2024年 40卷 831-850页

作者： Li, Guanrui Liu, Xinyang Loianno, Giuseppe NYU Tandon Sch Engn Brooklyn NY 11201 USA

Low-cost autonomous micro aerial vehicles have great potential to help humans by simplifying and speeding up complex tasks, such as construction, package delivery, and search and rescue. These systems, which may consist of single or multiple vehicles, can be equipped with passive connection mechanisms, such as rigid links or cables for transportation and manipulation tasks. However, these systems are inherently complex. They are often underactuated and evolve in nonlinear manifold configuration spaces. In addition, the complexity escalates for systems with cable-suspended load due to the hybrid dynamics that vary with the cables' tension conditions. This article presents the first aerial transportation and manipulation simulator incorporating different payloads and passive connection mechanisms with full system dynamics, planning, and control algorithms. Furthermore, it includes a novel general model accounting for the transient hybrid dynamics for aerial systems with cable-suspended load to closely mimic real-world systems. The availability of a flexible and intuitive interface further contributes to its usability and versatility. Comparisons between simulations and real-world experiments with different vehicles' configurations show the fidelity of the simulator results with respect to real-world settings. The experiments also show the simulator's benefit for the rapid prototyping and transitioning of aerial transportation and manipulation systems to real-world deployment.

关键词： Payloads Robots Transportation Mathematical models Collision avoidance Quadrotors Numerical models aerial robotics aerial systems and applications aerial transportation and manipulation micro aerial vehicles (MAVs) simulation

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Automatic 2-D LiDAR geometric calibration of installation bias

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robotics AND AUTONOMOUS SYSTEMS 2014年第8期62卷 1116-1129页

作者： Guerreiro, Bruno J. Silvestre, Carlos Oliveira, Paulo Univ Lisbon Inst Super Tecn Inst Syst & Robot P-1699 Lisbon Portugal Univ Macau Fac Sci & Technol Dept Elect & Comp Engn Taipa Peoples R China

This paper proposes two estimation algorithms for the determination of the attitude installation matrix for 2-D light detection and ranging (LiDAR) systems on board unmanned aerial vehicles (UAVs). While a comparative calibration algorithm assumes the existence of a known calibration surface, an automatic calibration algorithm does not require any prior knowledge of the trajectories of the vehicle or the terrain where the calibration mission is performed. The proposed calibration algorithms rely on the minimization of the errors between the measured point cloud and a representation of the known calibration surface or, alternatively, the errors between several acquired point clouds, by comparing each measured point cloud with a surface representation of the others. The resulting optimization problems are addressed using two techniques: (i) nonlinear optimization, where the attitude installation rotation matrix is parameterized by the ZYX Euler angles, and (ii) optimization on Riemannian manifolds, enabling the estimation of the attitude installation matrix on the group of special orthogonal matrices sO(3). The proposed calibration techniques are extensively validated and compared using both simulated and experimental LiDAR data sets, demonstrating their accuracy and performance. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Calibration Range sensing Special orthogonal group Mapping aerial robotics

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Multi-Objective Design Optimization of a Hexa-Rotor With Disturbance Rejection Capability Using an Evolutionary Algorithm

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IEEE ACCESS 2018年 6卷 69064-69074页

作者： Manuel Arellano-Quintana, Victor Alfredo Portilla-Flores, Edgar Alejandro Merchan-Cruz, Emmanuel Inst Politecn Nacl ESIME Azcapotzalco Mexico City 02250 DF Mexico Inst Politecn Nacl CIDETEC GUM Mexico City 07700 DF Mexico

In this paper, a methodology to design a hexa-rotor with the capability to reject disturbances using tilted propellers is presented. The methodology proposes the use of a robustness index as a measurement of the capability to reject external disturbances. Moreover, an energy index is proposed as a measurement of the energy consumed by the hexa-rotor in hovering. It is shown that the robustness index is opposed to this energy index. Therefore, a multi-objective optimization problem is proposed in which the objective functions are the robustness index and the energy index. This problem is solved with the help of an evolutionary algorithm with a Pareto approach. Three solutions are selected from the Pareto front and tested with a proposed controller in order to show the feasibility of the methodology. Finally, the design that has a better tradeoff between the two objectives is simulated with Gaussian noise and with the maximum disturbance that is capable of rejecting.

关键词： Design optimization evolutionary algorithms aerial robotics multi-objective optimization robust design

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Formation Control of Mobile Robots Using Multiple aerial Cameras

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IEEE TRANSACTIONS ON robotics 2015年第4期31卷 1064-1071页

作者： Aranda, Miguel Lopez-Nicolas, Gonzalo Saguees, Carlos Mezouar, Youcef Univ Zaragoza Inst Invest Ingn Aragon Zaragoza 50018 Spain Clermont Univ IFMA Inst Pascal F-63000 Clermont Ferrand France

This paper describes a new vision-based control method to drive a set of robots moving on the ground plane to a desired formation. As the main contribution, we propose to use multiple camera-equipped unmanned aerial vehicles (UAVs) as control units. Each camera views, and is used to control, a subset of the ground team. Thus, the method is partially distributed, combining the simplicity of centralized schemes with the scalability and robustness of distributed strategies. Relying on a homography computed for each UAV-mounted camera, our approach is purely image-based and has low computational cost. In the control strategy we propose, if a robot is seen by multiple cameras, it computes its motion by combining the commands it receives. Then, if the intersections between the sets of robots viewed by the different cameras satisfy certain conditions, we formally guarantee the stabilization of the formation, considering unicycle robots. We also propose a distributed algorithm to control the camera motions that preserves these required overlaps, using communications. The effectiveness of the presented control scheme is illustrated via simulations and experiments with real robots.

关键词： aerial robotics distributed robot systems formation control vision-based control wheeled robots

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Design and optimal control of a tiltrotor micro-aerial vehicle for efficient omnidirectional flight

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2020年第10-11期39卷 1305-1325页

作者： Allenspach, Mike Bodie, Karen Brunner, Maximilian Rinsoz, Luca Taylor, Zachary Kamel, Mina Siegwart, Roland Nieto, Juan Swiss Fed Inst Technol Zurich Switzerland

Omnidirectional micro-aerial vehicles (MAVs) are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and high hover efficiency have been developed independently, a robust system that combines the two has not been demonstrated to date. This paper presents the design and optimal control of a novel omnidirectional vehicle that can exert a wrench in any orientation while maintaining efficient flight configurations. The system design is motivated by the result of a morphology design optimization. A six-degree-of-freedom optimal controller is derived, with an actuator allocation approach that implements task prioritization, and is robust to singularities. Flight experiments demonstrate and verify the system's capabilities.

关键词： aerial robotics optimal control omnidirectional MAV tiltrotor design optimization

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Overview obstacle maps for obstacle-aware navigation of autonomous drones

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JOURNAL OF FIELD robotics 2019年第4期36卷 734-762页

作者： Pestana, Jesus Maurer, Michael Muschick, Daniel Hofer, Manuel Fraundorfer, Friedrich Graz Univ Technol TU Graz Inst Comp Graph & Vis ICG Inffeldgasse 16-2 A-8010 Graz Austria BIOENERGY2020 GmbH Graz Austria

Achieving the autonomous deployment of aerial robots in unknown outdoor environments using only onboard computation is a challenging task. In this study, we have developed a solution to demonstrate the feasibility of autonomously deploying drones in unknown outdoor environments, with the main capability of providing an obstacle map of the area of interest in a short period of time. We focus on use cases where no obstacle maps are available beforehand, for instance, in search and rescue scenarios, and on increasing the autonomy of drones in such situations. Our vision-based mapping approach consists of two separate steps. First, the drone performs an overview flight at a safe altitude acquiring overlapping nadir images, while creating a high-quality sparse map of the environment by using a state-of-the-art photogrammetry method. Second, this map is georeferenced, densified by fitting a mesh model and converted into an Octomap obstacle map, which can be continuously updated while performing a task of interest near the ground or in the vicinity of objects. The generation of the overview obstacle map is performed in almost real time on the onboard computer of the drone, a map of size 100mx75m is created in approximate to 2.75min, therefore, with enough time remaining for the drone to execute other tasks inside the area of interest during the same flight. We evaluate quantitatively the accuracy of the acquired map and the characteristics of the planned trajectories. We further demonstrate experimentally the safe navigation of the drone in an area mapped with our proposed approach.

关键词： aerial robotics computer vision mapping planning

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A Modular Framework for Motion Planning Using Safe-by-Design Motion Primitives

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IEEE TRANSACTIONS ON robotics 2019年第5期35卷 1233-1252页

作者： Vukosavljev, Marijan Kroeze, Zachary Schoellig, Angela P. Broucke, Mireille E. Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 1A1 Canada Univ Toronto Inst Aerosp Studies N York ON M3H 5T6 Canada

In this paper, we present a modular framework for solving a motion planning problem among a group of robots. The proposed framework utilizes a finite set of low-level motion primitives to generate motions in a gridded workspace. The constraints on allowable sequences of motion primitives are formalized through a maneuver automaton. At the high level, a control policy determines which motion primitive is executed in each box of the gridded workspace. We state general conditions on motion primitives to obtain provably correct behavior so that a library of safe-by-design motion primitives can be designed. The overall framework yields a highly robust design by utilizing feedback strategies at both the low and high levels. We provide specific designs for motion primitives and control policies suitable for multirobot motion planning;the modularity of our approach enables one to independently customize the designs of each of these components. Our approach is experimentally validated on a group of quadrocopters.

关键词： aerial robotics hybrid systems motion primitives planning and control for multiple mobile robots

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FLIE: First-Look Enabled Inspect-Explore Autonomy Toward Visual Inspection of Unknown Distributed and Discontinuous Structures

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IEEE ACCESS 2023年 11卷 28140-28150页

作者： Viswanathan, Vignesh Kottayam Satpute, Sumeet Gajanan Nikolakopoulos, George Lulea Univ Technol Dept Comp Sci Elect & Space Engn S-97187 Lulea Sweden

In this article, the problem of an online autonomous aerial inspection, specifically for discontinuous and distributed objects is presented. The proposed approach imposes view culling and photogrammetric constraints based on a geometrically modeled three-dimensional view pyramid, a view cone to filter surfaces by desired observation angle, a framework-integrated passive collision-avoidance scheme with the object under inspection, and a dynamically enveloping bounding-box region to map the visited surfaces. Furthermore, the proposed inspect-explore framework is validated for the case of an unknown environment with no prior knowledge of the object model under inspection. The overall inspection scheme is based on the novel First-Look approach, enabling the UAV to progressively adapt its inspection path to match the profile of the structure autonomously. The implemented exploration strategy imposes a tiered policy enabling the UAV to search, identify and navigate towards the structure for inspection. The presented work utilizes a unified architecture of the aforementioned inspect-explore framework to improve situational awareness in a previously unknown environment by enabling the UAV to explore its surrounding space and identify structures to execute closer inspection tasks. Extended simulations to evaluate the efficacy of the proposed inspect-explore framework are presented with multiple structure scenarios.

关键词： Inspection Visualization Autonomous aerial vehicles Robots Three-dimensional displays Planning Search problems Online services VIsualization Visual inspection aerial robotics distributed objects first-look online planning unknown environment

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Fast, autonomous flight in GPS-denied and cluttered environments

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JOURNAL OF FIELD robotics 2018年第1期35卷 101-120页

作者： Mohta, Kartik Watterson, Michael Mulgaonkar, Yash Liu, Sikang Qu, Chao Makineni, Anurag Saulnier, Kelsey Sun, Ke Zhu, Alex Delmerico, Jeffrey Karydis, Konstantinos Atanasov, Nikolay Loianno, Giuseppe Scaramuzza, Davide Daniilidis, Kostas Taylor, Camillo Jose Kumar, Vijay Univ Penn GRASP Lab Philadelphia PA 19146 USA Univ Zurich Robot & Percept Grp Zurich Switzerland

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development and present results from extensive experimental testing in real-world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS-denied environments.

关键词： aerial robotics collision avoidance field robots localization mapping motion and path planning motion control sensor fusion

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