Communication Efficiency in Information Gathering through Dynamic Information Flow

This thesis addresses the problem of how to improve the performance of multi-robot information gathering tasks by actively controlling the rate of communication between robots. Examples of such tasks include cooperative tracking and cooperative environmental monitoring. Communication is essential in such systems for both decentralised data fusion and decision making, but wireless networks impose capacity constraints that are frequently overlooked. While existing research has focussed on improving available communication throughput, the aim in this thesis is to develop algorithms that make more efficient use of the available communication capacity. Since information may be shared at various levels of abstraction, another challenge is the decision of where information should be processed based on limits of the computational resources available. Therefore, the flow of information needs to be controlled based on the trade-off between communication limits, computation limits and information value. In this thesis, we approach the trade-off by introducing the dynamic information flow (DIF) problem. We suggest variants of DIF that either consider data fusion communication independently or both data fusion and decision making communication simultaneously. For the data fusion case, we propose efficient decentralised solutions that dynamically adjust the flow of information. For the decision making case, we present an algorithm for communication efficiency based on local LQ approximations of information gathering problems. The algorithm is then integrated with our solution for the data fusion case to produce a complete communication efficiency solution for information gathering. We analyse our suggested algorithms and present important performance guarantees. The algorithms are validated in a custom-designed decentralised simulation framework and through field-robotic experimental demonstrations

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Reliable automatic camera-laser calibration

Camera-laser calibration is necessary for many robotics and computer vision applications. However, existing calibration toolboxes still require laborious effort from the operator in order to achieve reliable and accurate results. This paper proposes algorithms that augment two existing trustful calibration methods with an automatic extraction of the calibration object from the sensor data. The result is a complete procedure that allows for automatic camera-laser calibration. The first stage of the procedure is automatic camera calibration which is useful in its own right for many applications. The chessboard extraction algorithm it provides is shown to outperform openly available techniques. The second stage completes the procedure by providing automatic camera-laser calibration. The procedure has been verified by extensive experimental tests with the proposed algorithms providing a major reduction in time required from an operator in comparison to manual methods

Thermomechanical Fatigue Crack Growth Simulation in a Turbo-Housing Model Using Nonlinear Fracture Mechanics

Turbocharger housings in internal combustion engines are subjected to severe mechanical and thermal cyclic loads throughout their life-time or during engine testing. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermo-mechanical fatigue (TMF) of the material. For the computational TMF life assessment of high temperature components, the DTMF model can provide reliable TMF life predictions. The model is based on a short fatigue crack growth law and uses local finite-element (FE) results to predict the number of cycles to failure for a technical crack. In engine applications, it is nowadays often acceptable to have short cracks as long as they do not propagate and cause loss of function of the component. Thus, it is necessary to predict not only potential crack locations and the corresponding number of cycles for a technical crack, but also to determine subsequent crack growth or even a possible crack arrest. In this work, a method is proposed that allows the simulation of TMF crack growth in high temperature components using FE simulations and non-linear fracture mechanics (NLFM). A NLFM based crack growth simulation method is described. This method starts with the FE analysis of a component. In this paper, the method is demonstrated for an automotive turbocharger housing subjected to TMF loading. A transient elastic-viscoplastic FE analysis is used to simulate four heating and cooling cycles of an engine test. The stresses, inelastic strains, and temperature histories from the FEA are then used to perform TMF life predictions using the standard DTMF model. The crack position and the crack plane of critical hotspots are then identified. Simulated cracks are inserted at the hotspots. For the model demonstrated, cracks were inserted at two hotspot locations. The ΔJ integral is computed as a fracture mechanics parameter at each point along the crack-front, and the crack extension of each point is then evaluated, allowing the crack to grow iteratively. The paper concludes with a comparison of the crack growth curves for both hotspots with experimental results

A Mechanism-Based Thermomechanical Fatigue Life Assessment Method for High Temperature Engine Components with Gradient Effect Approximation

High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length. In the presence of significant gradients of stresses, strains, and temperatures, the use of surface field values could lead to very conservative estimates of TMF life when compared with reported lives from hardware testing. As an approximation of gradient effects, a non-local approach of the DTMF model is applied. This approach considers through-thickness fields where the micro-crack growth law is integrated through the thickness considering these variable fields. With the help of software tools, this method is automated and applied to components with complex geometries and fields. It is shown, for the TMF life prediction of a turbocharger housing, that the gradient correction using the non-local approach leads to more realistic life predictions and can distinguish between surface cracks that may arrest or propagate through the thickness and lead to component failure