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Eric Feron

Publications and source records attributed to Eric Feron.

At least 55 records · Page 3Linked to original sources

On the Design and Optimization of an Autonomous Microgravity Enabling Aerial Robot

This paper describes the process and challenges behind the design and development of a micro-gravity enabling aerial robot. The vehicle, designed to provide at minimum 4 seconds of micro-gravity at an accuracy of .001 g's, is designed with suggestions and constraints from both academia and industry as well a regulatory agency. The feasibility of the flight mission is validated using a simulation environment, where models obtained from system identification of existing hardware are implemented to increase the fidelity of the simulation. The current development of a physical test bed is described. The vehicle employs both control and autonomy logic, which is developed in the Simulink environment and executed in a Pixhawk flight control board.

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The Robotarium: A remotely accessible swarm robotics research testbed

This paper describes the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-robot research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium and discusses the considerations one must take when making complex hardware remotely accessible. In particular, safety must be built into the system already at the design phase without overly constraining what coordinated control programs users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.

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Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.

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Passenger Flow Predictions at Sydney International Airport: A Data-Driven Queuing Approach

Time spent in processing zones at an airport are an important part of the passenger's airport experience. It undercuts the time spent in the rest of the airport, and therefore the revenue that could be generated from shopping and dining. It can also result in passengers missing flights and connections, which has significant operational repercussions. Inadequate staffing levels are often to blame for large congestion at an airport. In this paper, we present a stochastic simulation that estimates the operational uncertainty in passenger processing at immigration. Congestion and delays are estimated on arrivals and departures based on scheduled flight departures and arrivals. We demonstrate the use of cellular tracking data in refining the model, and an approach to controlling congestion by adjusting staffing levels.

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Anatomy of a Crash

Transportation networks constitute a critical infrastructure enabling the transfers of passengers and goods, with a significant impact on the economy at different scales. Transportation modes, whether air, road or rail, are coupled and interdependent. The frequent occurrence of perturbations on one or several modes disrupts passengers' entire journeys, directly and through ripple effects. The present paper provides a case report of the Asiana Crash in San Francisco International Airport on July 6th 2013 and its repercussions on the multimodal transportation network. It studies the resulting propagation of disturbances on the transportation infrastructure in the United States. The perturbation takes different forms and varies in scale and time frame : cancellations and delays snowball in the airspace, highway traffic near the airport is impacted by congestion in previously never congested locations, and transit passenger demand exhibit unusual traffic peaks in between airports in the Bay Area. This paper, through a case study, aims at stressing the importance of further data-driven research on interdependent infrastructure networks for increased resilience. The end goal is to form the basis for optimization models behind providing more reliable passenger door-to-door journeys.

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Credible Autocoding of Convex Optimization Algorithms

The efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work.

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A Complete framework for ambush avoidance in realistic environments

Operating vehicles in adversarial environments between a recurring origin-destination pair requires new planning techniques. A two players zero-sum game is introduced. The goal of the first player is to minimize the expected casualties undergone by a convoy. The goal of the second player is to maximize this damage. The outcome of the game is obtained via a linear program that solves the corresponding minmax optimization problem over this outcome. Different environment models are defined in order to compute routing strategies over unstructured environments. To compare these methods for increasingly accurate representations of the environment, a grid-based model is chosen to represent the environment and the existence of a sufficient network size is highlighted. A global framework for the generation of realistic routing strategies between any two points is described. This framework requires a good assessment of the potential casualties at any location, therefore the most important parameters are identified. Finally the framework is tested on real world environments.

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Formally expressing the semantics of observer-based fault detection software

The aim is to create reliable and verifiable fault detection software to detect abrupt changes in safety-critical dynamic systems. Fault detection methods are implemented as software on digital computers that monitor and control the system. We implement three observer-based fault detection methods on a 3 degrees of freedom (3DOF) laboratory helicopter, in the form of software. We examine the performance of those methods to detect different faults during flight in a closed-loop setup. All selected methods show acceptable detection performance. However, it is not possible to repeat the test for every possible conditions, inputs and fault scenarios. In this paper, we translate fault detection properties and mathematical proofs into a formal language, previously used in software validation and verification. We include the translated properties in software in the form of non-executable annotations that can be read by machine. Consequently, some high level functional properties of the code can be verified by automatic software verification tools. This certifies fault detection software for a set of bounded data and increases the reliability in practice.

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Verifiable Control System Development for Gas Turbine Engines

A control software verification framework for gas turbine engines is developed. A stability proof is presented for gain scheduled closed-loop engine system based on global linearization and linear matrix inequality (LMI) techniques. Using convex optimization tools, a single quadratic Lyapunov function is computed for multiple linearizations near equilibrium points of the closed-loop system. With the computed stability matrices, ellipsoid invariant sets are constructed, which are used efficiently for DGEN turbofan engine control code stability analysis. Then a verifiable linear gain scheduled controller for DGEN engine is developed based on formal methods, and tested on the engine virtual test bench. Simulation results show that the developed verifiable gain scheduled controller is capable of regulating the engine in a stable fashion with proper tracking performance.

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A Message Passing Strategy for Decentralized Connectivity Maintenance in Agent Removal

In a multi-agent system, agents coordinate to achieve global tasks through local communications. Coordination usually requires sufficient information flow, which is usually depicted by the connectivity of the communication network. In a networked system, removal of some agents may cause a disconnection. In order to maintain connectivity in agent removal, one can design a robust network topology that tolerates a finite number of agent losses, and/or develop a control strategy that recovers connectivity. This paper proposes a decentralized control scheme based on a sequence of replacements, each of which occurs between an agent and one of its immediate neighbors. The replacements always end with an agent, whose relocation does not cause a disconnection. We show that such an agent can be reached by a local rule utilizing only some local information available in agents' immediate neighborhoods. As such, the proposed message passing strategy guarantees the connectivity maintenance in arbitrary agent removal. Furthermore, we significantly improve the optimality of the proposed scheme by incorporating $δ$-criticality (i.e. the criticality of an agent in its $δ$-neighborhood).

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Online Performance Optimization of a DC Motor Driving a Variable Pitch Propeller

A practical online optimization scheme is developed for performance optimization of an electrical aircraft propulsion system. The goal is to minimize the power extraction of the propulsion system for any given thrust value. The online optimizer computes the optimum pitch angle of a variable pitch propeller by minimizing the power of the system for a command thrust value. This algorithm is tested on a DC motor driving a variable pitch propeller; the experimental hardware setup of the DC motor along with its variable pitch propeller is also described. Experimental results show the efficiency and practicality of the proposed online optimization scheme. Outstanding issues are sketched.

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Numerical Analysis of Gate Conflict Duration and Passenger Transit Time in Airport

Robustness is as important as efficiency in air transportation. All components in the air traffic system are connected to form an interactive network. So, a disturbance that occurs in one component, for example, a severe delay at an airport, can influence the entire network. Delays are easily propagated between flights through gates, but the propagation can be reduced if gate assignments are robust against stochastic delays. In this paper, we analyze gate delays and suggest an approach that involves assigning gates while making them robust against stochastic delays. We extract an example flight schedule from data source and generate schedules with increased traffic to analyze how the compact flight schedules impact the robustness of gate assignment. Simulation results show that our approach improves the robustness of gate assignment. Particularly, the robust gate assignment reduces average duration of gate conflicts by 96.3% and the number of gate conflicts by 96.7% compared to the baseline assignment. However, the robust gate assignment results in longer transit time for passengers, and a trade-off between the robustness of gate assignment and passenger transit time is presented.

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Automated, Credible Autocoding of An Unmanned Aggressive Maneuvering Car Controller

This article describes the application of a credible autocoding framework for control systems towards a nonlinear car controller example. The framework generates code, along with guarantees of high level functional properties about the code that can be independently verified. These high-level functional properties not only serves as a certificate of good system behvaior but also can be used to guarantee the absence of runtime errors. In one of our previous works, we have constructed a prototype autocoder with proofs that demonstrates this framework in a fully automatic fashion for linear and quasi-nonlinear controllers. With the nonlinear car example, we propose to further extend the prototype's dataflow annotation language environment with with several new annotation symbols to enable the expression of general predicates and dynamical systems. We demonstrate manually how the new extensions to the prototype autocoder work on the car controller using the output language Matlab. Finally, we discuss the requirements and scalability issues of the automatic analysis and verification of the documented output code.

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From Design to Implementation: an Automated, Credible Autocoding Chain for Control Systems

This article describes a fully automated, credible autocoding chain for control systems. The framework generates code, along with guarantees of high level functional properties which can be independently verified. It relies on domain specific knowledge and fomal methods of analysis to address a context of heightened safety requirements for critical embedded systems and ever-increasing costs of verification and validation. The platform strives to bridge the semantic gap between domain expert and code verification expert. First, a graphical dataflow language is extended with annotation symbols enabling the control engineer to express high level properties of its control law within the framework of a familiar language. An existing autocoder is enhanced to both generate the code implementing the initial design, but also to carry high level properties down to annotations at the level of the code. Finally, using customized code analysis tools, certificates are generated which guarantee the correctness of the annotations with respect to the code, and can be verified using existing static analysis tools. Only a subset of properties and controllers are handled at this point.

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Impact of Gate Assignment on Gate-Holding Departure Control Strategies

Gate holding reduces congestion by reducing the number of aircraft present on the airport surface at any time, while not starving the runway. Because some departing flights are held at gates, there is a possibility that arriving flights cannot access the gates and have to wait until the gates are cleared. This is called a gate conflict. Robust gate assignment is an assignment that minimizes gate conflicts by assigning gates to aircraft to maximize the time gap between two consecutive flights at the same gate; it makes gate assignment robust, but passengers may walk longer to transfer flights. In order to simulate the airport departure process, a queuing model is introduced. The model is calibrated and validated with actual data from New York La Guardia Airport (LGA) and a U.S. hub airport. Then, the model simulates the airport departure process with the current gate assignment and a robust gate assignment to assess the impact of gate assignment on gate-holding departure control. The results show that the robust gate assignment reduces the number of gate conflicts caused by gate holding compared to the current gate assignment. Therefore, robust gate assignment can be combined with gate-holding departure control to improve operations at congested airports with limited gate resources.

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Valuating Surface Surveillance Technology for Collaborative Multiple-Spot Control of Airport Departure Operations

Airport departure operations are a source of airline delays and passenger frustration. Excessive surface traffic is a cause of increased controller and pilot workload. It is also a source of increased emissions and delays, and does not yield improved runway throughput. Leveraging the extensive past research on airport departure management, this paper explores the environmental and safety benefits that improved surveillance technologies can bring in the context of gate- or spot-release strategies. The paper shows that improved surveillance technologies can yield 4% to 6% reduction of aircraft on taxiway, and therefore emissions, in addition to the savings currently observed by implementing threshold starategies under evaluation at Boston Logan Airport and other busy airports during congested periods. These calculated benefits contrast sharply with our previous work, which relied on simplified airport ramp areas with a single departure spot, and where fewer environmental and economic benefits of advanced surface surveillance systems could be established. Our work is illustrated by its application to New-York LaGuardia and Seattle Tacoma airports.

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Airport Gate Scheduling for Passengers, Aircraft, and Operation

Passengers' experience is becoming a key metric to evaluate the air transportation system's performance. Efficient and robust tools to handle airport operations are needed along with a better understanding of passengers' interests and concerns. Among various airport operations, this paper studies airport gate scheduling for improved passengers' experience. Three objectives accounting for passengers, aircraft, and operation are presented. Trade-offs between these objectives are analyzed, and a balancing objective function is proposed. The results show that the balanced objective can improve the efficiency of traffic flow in passenger terminals and on ramps, as well as the robustness of gate operations.

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Planning Random path distributions for ambush games in unstructured environments

Operating vehicles in adversarial environments require non-conventional planning techniques. A two-player, zero-sum non-cooperative game is introduced, which is solved via a linear program. An extension is proposed to construct networks displaying good representations of the environment characteristics, while offering acceptable results for the technique used. Sensitivity of the solution to the LP solver algorithm is identified. The performances of the planner are finally assessed by comparison with those of conventional planners. Results are used to formulate secondary objectives to the problem.

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