| 1. |
- Berlin, Jonas, et al.
(författare)
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Trajectory Generation for Mobile Robots in a Dynamic Environment using Nonlinear Model Predictive Control
- 2021
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2021-August, s. 942-947
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Konferensbidrag (refereegranskat)abstract
- This paper presents an approach to collision-free, long-range trajectory generation for a mobile robot in an industrial environment with static and dynamic obstacles. For the long-range planning a visibility graph together with A is used to find a collision-free path with respect to the static obstacles. This path is used as a reference path to the trajectory planning algorithm that in addition handles dynamic obstacles while complying with the robot dynamics and constraints. A Nonlinear Model Predictive Control (NMPC) solver generates a collision-free trajectory by staying close to the initial path but at the same time obeying all constraints. The NMPC problem is solved efficiently by leveraging the new numerical optimization method Proximal Averaged Newton for Optimal Control (PANOC). The algorithm was evaluated by simulation in various environments and successfully generated feasible trajectories spanning hundreds of meters in a tractable time frame.
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| 2. |
- Bertilsson, Filip, et al.
(författare)
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Centralized versus Distributed Nonlinear Model Predictive Control for Online Robot Fleet Trajectory Planning
- 2022
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2022-August, s. 701-706
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Konferensbidrag (refereegranskat)abstract
- In this paper, we formulate and evaluate a centralized vs. a distributed approach for online trajectory generation for a fleet of mobile robots in the presence of static and dynamic obstacles. Due to dynamic obstacles, the trajectories need to be updated online and this is formulated as a nonlinear model predictive control problem. We show that both centralized and distributed MPC solvers manage to generate smooth collision-free trajectories. The distributed approach is shown to scale to many robots very well. In contrast, the computational cost of the centralized approach increases with the number of robots. However, the trajectories generated by the distributed control approach have larger deviations than those generated by the centralized approach. The experiments suggest that the centralized method should be chosen with sufficient computation resource while the distributed approach is a viable alternative when the number of robots is considerable.
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| 3. |
- Ebrahimi, Amir Hossein, 1976, et al.
(författare)
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Modelling and analysis of product platforms and assembly sequences with respect to variability
- 2021
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2021-August, s. 563-569
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Konferensbidrag (refereegranskat)abstract
- A challenge for highly configurable products is that the manufacturing system has to support all possible variants that can be configured. The production system is often highly automated and the link between the product and the assembly system can be expressed through operations where each operation models how a part in the bill-of-material is assembled to the final product. Typically, operations have precedence constraints that express that certain parts have to be assembled before other parts. However, it is important to make sure that all possible variants can be successfully assembled while satisfying all precedence constraints. In this paper we present fully automated analysis method that is able to analyze the existence of product configurations of that cannot be successfully assembled.
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| 4. |
- Erös, Endre, 1990, et al.
(författare)
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Fault localization for intelligent automation systems
- 2023
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Ingår i: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - 1946-0740 .- 1946-0759. ; 2023-September
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Konferensbidrag (refereegranskat)abstract
- Conventional programming of explicit control code is unsuitable for flexible and collaborative production systems. A model-based approach, which focuses on defining capabilities of a system, instead of specifying how to achieve them, provides an alternative for creating complex, scalable, and reliable systems. This is accomplished through the use of behavior models, and tools such as planning, synthesis, verification, and testing. However, developing such models is not without challenges, as it is possible to overlook or incorrectly specify potential behavior and constraints. This can result in unsolvable planning problems or plans that are invalid for other reasons. When plans are unobtainable, developers receive no feedback, which makes model adjustments a difficult and time-intensive task. This paper recognizes these challenges as crucial barriers for adopting model-based development of intelligent automation systems. To facilitate the development of such systems, an approach for detecting and localizing faults in behavior models is presented. Drawing inspiration from software fault localization techniques, the proposed method involves identifying suspicious resources, variables, and operations. The effectiveness of this approach is illustrated with an example use case.
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| 5. |
- Erös, Endre, 1990, et al.
(författare)
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Structural Coverability for Intelligent Automation Systems
- 2023
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2023-August
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Konferensbidrag (refereegranskat)abstract
- In order to be flexible and handle complex scenarios, intelligent automation systems might benefit from automated planning techniques which rely on specifications and models describing their behavior. However, due to the presence of message passing, latency, jitter, timeouts, failures, and error handling, the verification of such behavior models using formal methods is often unfeasible. Therefore, testing has emerged as an approach to evaluating the behavior of intelligent automation systems. This paper presents a way to analyze structural coverability of behavior models for intelligent automation systems, which is inspired by the modified condition/decision coverage (MC/DC) criterion. This is paired with a testing procedure that enables each test case to influence both the controller and the simulated environment by injecting some specific state. As a result, the proposed coverability criterion can effectively identify segments of the behavior model that have not been adequately tested and suggest additional test cases to improve coverability. An example use case is presented to demonstrate the effectiveness of this approach.
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| 6. |
- Jernheden, Elinor, et al.
(författare)
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Comparison of Exact and Approximate methods for the Vehicle Routing Problem with Time Windows
- 2020
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2020-August, s. 378-383
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Konferensbidrag (refereegranskat)abstract
- This paper presents a comparison of two approaches for solving the vehicle routing problem with time windows (VRPTW). Scheduling of vehicles for pickup and delivery is a common problem in logistics and may be expressed as VRPTW, for which both exact and approximate techniques are available. It is therefore interesting to compare such techniques to evaluate their performance and figure what is the best option based on the instance features and size. In this work, we compared Mixed Integer Linear Programming (MILP) with Set-Based Particle Swarm optimization (S-PSO). Both algorithms are tested on the full 56 instances of the Solomon dataset. The results show that the two algorithms perform similarly for lower number of customers while there are significant differences for the cases with higher number of customers. For higher number of customers MILP consistently performs as good as or better than S-PSO for the clustered data, both with short and long scheduling horizons, while the S-PSO outperforms MILP in most cases with random and mixed random clustered data with long scheduling horizons. Furthermore when the algorithms perform the same with regards to the main objective (number of vehicles), MILP generally achieves a better result in the second objective (distance traveled).
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| 7. |
- Lidén Eddeland, Johan, 1991, et al.
(författare)
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Enhancing Temporal Logic Falsification with Specification Transformation and Valued Booleans
- 2020
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Ingår i: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. - 1937-4151 .- 0278-0070. ; 39:12, s. 5247-5260
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Tidskriftsartikel (refereegranskat)abstract
- Cyber-Physical Systems (CPSs) are systems with both physical and software components, for example cars and industrial robots. Since these systems exhibit both discrete and continuous dynamics, they are complex and it is thus difficult to verify that they behave as expected. Falsification of temporal logic properties is an approach to find counterexamples to CPSs by means of simulation. In this paper, we propose two additions to enhance the capability of falsification and make it more viable in a large-scale industrial setting. The first addition is a framework for transforming specifications from a signal-based model into Signal Temporal Logic. The second addition is the use of Valued Booleans and an additive robust semantics in the falsification process. We evaluate the performance of the additive robust semantics on a set of benchmark models, and we can see that which semantics are preferable depend both on the model and on the specification.
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| 8. |
- Lidén Eddeland, Johan, 1991, et al.
(författare)
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Evaluating Optimization Solvers and Robust Semantics for Simulation-Based Falsification
- 2020
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Ingår i: EPiC Series in Computing. - : EasyChair. - 2398-7340. ; 74, s. 259-266
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Konferensbidrag (refereegranskat)abstract
- Temporal-logic based falsification of Cyber-Physical Systems is a testing technique used to verify certain behaviours in simulation models, however the problem statement typically requires some model-specific tuning of parameters to achieve optimal results. In this experience report, we investigate how different optimization solvers and objective functions affect the falsification outcome for a benchmark set of models and specifications. With data from the four different solvers and three different objective functions for the falsification problem, we see that choice of solver and objective function depends both on the model and the specification that are to be falsified. We also note that using a robust semantics of Signal Temporal Logic typically increases falsification performance compared to using Boolean semantics.
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| 9. |
- Lidén Eddeland, Johan, 1991, et al.
(författare)
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Industrial Temporal Logic Specifications for Falsification of Cyber-Physical Systems
- 2020
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Ingår i: EPiC Series in Computing. - : EasyChair. - 2398-7340. ; 74, s. 267-274
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Konferensbidrag (refereegranskat)abstract
- In this benchmark proposal, we present a set of large specifications stated in Signal Temporal Logic (STL) intended for use in falsification of Cyber-Physical Systems. The main purpose of the benchmark is for tools that monitor STL specifications to be able to test their performance on complex specifications that have structure similar to industrial specifications. The benchmark itself is a Git repository which will therefore be updated over time, and new specifications can be added. At the time of submission, the repository contains a total of seven Simulink requirement models, resulting in 17 generated STL specifications.
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| 10. |
- Lidén Eddeland, Johan, 1991, et al.
(författare)
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Multi-Requirement Testing Using Focused Falsification
- 2022
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Ingår i: HSCC 2022 - Proceedings of the 25th ACM International Conference on Hybrid Systems: Computation and Control, Part of CPS-IoT Week 2022. - New York, NY, USA : ACM.
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Konferensbidrag (refereegranskat)abstract
- Testing of Cyber-Physical Systems (CPS) deals with the problem of finding input traces to the systems such that given requirements do not hold. Requirements can be formalized in many different ways; in this work requirements are modeled using Signal Temporal Logic (STL) for which a quantitative measure, or \emph{robustness value}, can be computed given a requirement together with input and output traces. This value is a measure of how far away the requirement is from not holding and is used to guide falsification procedures for deciding on new input traces to simulate one after the other. When the system under test has multiple requirements, standard approaches are to falsify them one-by-one, or as a conjunction of all requirements, but these approaches do not scale well for industrial-sized problems. In this work we consider testing of systems with multiple requirements by proposing focused multi-requirement falsification. This is a multi-stage approach where the solver tries to sequentially falsify the requirements one-by-one, but for every simulation also evaluate the robustness value for all requirements. After one requirement has been focused long enough, the next requirement to focus is selected by considering the robustness values and trajectory history calculated thus far. Each falsification attempt makes use of a prior sensitivity analysis, which for each requirement estimates the parameters that are unlikely to affect the robustness value, in order to reduce the number of parameters that are used by the optimization solver. The proposed approach is evaluated on a public benchmark example containing a large number of requirements, and includes a comparison of the proposed algorithm against a new suggested baseline method.
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