Henrik Schioler

It has been widely discussed whether the existence of other universes than the known universe is a purely metaphysical consideration. This paper argues to the contrary that the existence of other universes is a meaningful hypothesis, which can be tested based on observable data. The paper applies the perspective of observer bias as an approach for assigning probabilities to the mutually excluding hypotheses of universe vs. multiverse, i.e., whether the known universe is the only universe, or just one universe in an ensemble of universes, a so-called multiverse. The basic idea of the paper relies on the following consideration. In a multiverse, the vast majority of observers would live in universes that are more life friendly. Thus, conditional on there being a multiverse, we should expect to find ourselves in a universe with values of the fundamental parameters that provide particularly fertile grounds for life. In contrast, if there is only a single universe, it may well be the case that there is still a few observers even if the parameters are far from ideal for life, and in that case, those observers will find values of the parameters that are not ideal for intelligent life. It may well be the case that, among all parameter configurations that allow life at least somewhere, those that are not ideal for life far outnumber those that are ideal for life. Based on this elementary consideration, the paper proceeds to propose a quantitative framework to determine probabilities for either hypothesis. In particular, it is described how a future ab initio determination of some of the factors in the Drake equation may be used to infer which one of the two hypotheses is the more likely. A quantitative approach to this end is proposed. Expressing these factors of the Drake equation in the context of the two hypotheses, a general likelihood approach is first described. Then, to support intuition, example computations are provided, illustrating how an actual hypothesis test would work in practice.

Evaluations of different technologies and solutions for indoor localization exist but only a few are aimed at the industrial context. In this paper, we compare and analyze two prominent solutions based on Ultra Wide Band Radio (Pozyx) and Ultrasound (GoT), both installed in an industrial manufacturing laboratory. The comparison comprises a static and a dynamic case. The static case evaluates average localization errors over 90 s intervals for 100 ground-truth points at three different heights, corresponding to different relevant objects in an industrial environment: mobile robots, pallets, forklifts and worker helmets. The average error obtained across the laboratory is similar for both systems and is between 0.3 m and 0.6 m, with higher errors for low altitudes. The dynamic case is performed with a mobile robot travelling with an average speed of 0.5 m/s at a height of 0.3 m. In this case, low frequency error components are filtered out to focus the comparison on dynamic errors. Average dynamic errors are within 0.3–0.4 m for Pozyx and within 0.1–0.2 m for GoT. Results show an acceptable accuracy required for tracking people or objects and could serve as a guideline for the least achievable accuracy when applied for mobile robotics in conjunction with other elements of a robotic navigation stack.

Integrated Modular Avionics enables applications of different criticality levels to share the same hardware platform with an established temporal and spatial isolation. On-chip communication systems for such platforms must support different bandwidth and latency requirements of applications while preserving time predictability. In this paper, our concern is a time-predictable on-chip network architecture for targeting applications in mixed-criticality aerospace systems. The proposed architecture introduces a mixed, priority-based and time-division-multiplexed arbitration scheme to accommodate different bandwidth and latency in the same network while preserving worst-case time predictability for end-to-end communication without packet loss. Furthermore, as isolation of erroneous transmission by a faulty application is a key aspect of contingency management, the communication system should support isolation mechanisms to prevent interference. For this reason, a sampling port and isolated sampling buffer-based approach is proposed with a transmission authorisation control mechanism, guaranteeing spatial and temporal isolation between communicating systems.

Unmanned aircrafts (UA) usually fly below 500 ft to be segregated from manned aircraft. However, while general aviation (GA) usually do fly above 500 ft in areas where UA are allowed to operate, GA will at times also fly below 500 ft. Consequently, there is a distinct risk of near‐miss encounters as well as actual midair collisions (MACs). This work presents a model for determining this risk based on physical parameters of the aircraft and actual figures for the numbers of GA in a given airspace, as well as the probability of having GA below 500 ft. The aim is to achieve a prediction with a precision better than one order of magnitude relative to the true MAC rate value. The model is applied to Danish airspace and the MAC rate for unmitigated operations of UA is found to be approximately 10⁻⁶ MAC per flight hour. The model is particularly well suited for beyond visual line‐of‐sight operations, and is useful for UA operators for conducting risk assessment of planned operations as well as for regulators for determining appropriate operational requirements.

This paper presents a controller design for Unmanned Aerial Vehicles (UAV) of multi-rotor type, where global positioning is only intermittently available. The developed controllers are of state-space/observer type with switching, where discrete modes are determined by the momentary availability of absolute geographical localization. Control design is based on a generalized concept of stochastic ε-moment stability and conducted towards optimal robustness towards measurement intermittency. A simplistic but frequently applied mechanical model of the UAV under control, as well as the onboard inertial measurement unit (IMU), is presented and used as a basis for the proposed design methodology. Test flight results are presented with artificial measurement intermittency demonstrating the robustness of the designed controller.

We consider the case of fleet management of a moderate number of Unmanned Aerial Vehicles (UAV or UAS) in confined space, e.g. indoor. Indoor operation of UAVs requires indoor localization capabilities as well as a sufficiently precise 3D map of the facility, whereas fleet management of multiple UAV adds an extra dimension of complexity. Additional complexity is mainly introduced by constraints ensuring collision free operation. Based on earlier work on mapping, path planning and localization we suggest fleet management through a Timed Game formulation and Winning Strategy controller synthesis using the tool Uppaal Tiga.