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Multi-robot simultaneous localization and mapping (SLAM) is a fundamental task in multi-robot operations. Robots must have a common understanding of their location and that of their team members to complete coordinated actions. However, multi-robot SLAM between Uncrewed Surface Vessels (USVs) and Autonomous Underwater Vehicles (AUVs) has primarily been achieved through acoustic pinging between robots to retrieve range measurements; a measurement technique requires that robots to be in similar locations simultaneously, have an uninterrupted path for signal propagation, and may necessitate synchronized clocks. This is especially challenging in complex, cluttered maritime environments, where structures may impede signals. However, these same structures may be observable above and below the water's surface, presenting an opportunity for inter-robot SLAM loop closure between USV and AUV data streams. This work builds upon recent research on inter-robot SLAM loop closure between USV and AUV data cite{msm}, extending it to propose a centralized multi-robot SLAM system. Each robot performs its state estimation, and we detect loop closures between each AUV and the USV data. These inter-robot loop closures are used to merge each robot's state estimate into a centralized graph, yielding estimates for the whole time history of the USV and all AUVs in the system. Validation is performed using real-world perceptual data in three different environments. Results show improved errors for AUVs in the multi-robot SLAM system compared to single-robot SLAM over the same trajectories. To our knowledge, this is the first instance of a multi-robot SLAM system with AUVs and USVs built on loop closures rather than acoustic distance measurements.
We show that cyclic permutations avoiding 321 are precisely those permutations whose image under the fundamental bijection avoid a set of vincular patterns. We do this by using pattern functions and arrow patterns, in combination with the characterization of 321 avoidance in terms of equality of the upper bound of the Daiconis-Graham inequalities. We then explore some consequences of this result, including upper and lower bound results on the growth rate of 321 avoiding cycles.
The physical properties of mixtures of fuel components can aid researchers who are developing surrogate mixtures for fuels and modeling the combustion process. This work reports the densities, speeds of sound, and viscosities of mixtures of tridecane with n-alkylbenzenes. Densities, speeds of sound, and viscosities increased with decreasing temperature and an increase in the component with the higher property value, except for ethylbenzene's and propylbenzene's speeds of sound where minima were found in mixtures. As n-alkylbenzene size increased, excess speeds of sound (c E's) increased, and excess isentropic compressibilities (Kappa s E's) and excess molar volumes (V m E's) decreased. A positive slope was found in the relationship between the Kappa s E's and V m E's of equimolar mixtures of tridecane and n-alkylbenzenes, which highlights the importance of molar packing and volume changes on compressibility. The mixture bulk moduli span a wide range of values, which would impact their resulting engine combustion behavior. Also, many of the mixture densities fell with the ASTM jet fuel specification. These data will help scientists and engineers who are designing surrogate fuel mixtures and modeling engine combustion processes.
The addition of alcohols to fuels is one approach to reducing the amount of carbon in fuel sources, and thus the impact of alcohols on engine components needs to be evaluated. This work investigated the effect of adding alcohols to jet fuel (JP-5) on the swelling and tensile strength of commercially produced Buna-N O-rings and additively manufactured (AM) acrylate O-rings. O-rings were exposed to JP-5, pure alcohols (methanol to n-octanol), and alcohol mixtures up to 30 % for seven days. The volume percentage swells ranged from -1 to 58 %. The AM O-rings swelled more in the pure alcohols (>46 %) than in JP-5 (17 %), while the Buna-N O-rings swelled more in the JP-5 (25 %) than in the alcohols (< 9 %). For Buna-N, the volume change of the larger alcohols was greater (similar to 8 %) than those of the smaller alcohols (<5 %), while no specific trend was seen for the AM O-rings. For the Buna-N O-rings all of the blends of alcohol and JP-5 produced larger volume increases than those induced by the alcohol or JP-5 alone. This also occurred for the higher concentrations of alcohol blends with the AM O-rings. The swelling reduced the tensile strength of the O-rings by as much as 60 % for the Buna-N O-rings and 88 % for the AM O-rings. Evaporation of the alcohols from the O-rings for three weeks or more caused the Buna-N O-rings to shrink by up to 11 % and for the tensile strength to increase by around 26 %. The shrinkage was less for the AM O-ring (similar to 3 %), but the increases in tensile strength ranged from 10 to 50 %. The synergistic behaviour of alcohols and fuels to enhance O-ring swelling found in this study encourages those selecting O-rings for a particular application to conduct testing on the actual fuel blends.
Recently, we introduced a coherent framework for interval-valued probability measures, providing a rigorous foundation for modeling imprecise probabilities and uncertainty in a natural and internally consistent manner. Building upon this foundation, the present paper develops a detailed analysis of the underlying theoretical structure, highlighting in particular some distinctive features of the theory of Intuitionistic Fuzzy Sets and introducing a new concept of conditional imprecise probability.In particular, we propose an updating rule for events that incorporates fundamental notions of statistical independence together with suitable product constructions for imprecise probability measures.Finally, these concepts are employed to define the notions of independent and incompatible random variables within the proposed framework, and to provide a refined interpretation of the classical umbrella problem.
