In the era of humanoid robotics, navigation and path planning of humanoids in complex environments have always remained as one of the most promising area of research. In this paper, a novel hybridized navigational controller is proposed using the logic of both classical technique and computational intelligence for path planning of humanoids. The proposed navigational controller is a hybridization of regression analysis with adaptive particle swarm optimization. The inputs given to the regression controller are in the forms of obstacle distances, and the output of the regression controller is interim turning angle. The output interim turning angle is again fed to the adaptive particle swarm optimization controller along with other inputs. The output of the adaptive particle swarm optimization controller termed as final turning angle acts as the directing factor for smooth navigation of humanoids in a complex environment. The proposed navigational controller is tested for single as well as multiple humanoids in both simulation and experimental environments. The results obtained from both the environments are compared against each other, and a good agreement between them is observed. Finally, the proposed hybridization technique is also tested against other existing navigational approaches for validation of better efficiency.

Pine wood nematode (Bursaphelenchus xylophilus) (Aphelenchida: Parasitaphelencidae) is one of the most harmful agents in coniferous forests. The most important vectors of pine wood nematode are considered to be some Monochamus species (Col.: Cerambycidae), which had been forest insects with secondary importance before the appearance of B. xylophilus. However, the continuous spreading of the nematode has changed this status and necessitated detailed biological and climatological investigation of the main European vector, Monochamus galloprovincialis. The potential distribution area of M. galloprovincialis involves those areas where the risk of the appearance of pine wood nematode B. xylophilus is significant. The main objective of our analysis was to obtain information about the influencing effects of North Atlantic Oscillation (NAO) on the potential European range of B. xylophilus and its vector species M. galloprovincialis based on the connection between the mean temperature of July in Europe, the distribution of day-degrees of the vector and the NAO index. Our assessment was based on fundamental biological constants of the nematode and the cerambycid pest as well as the ECMWF ERA5 Global Atmospheric Reanalysis dataset. Our hypothesis was built on the fact that the monthly mean temperature had to exceed 20°C in the interest of an efficient expansion of the nematode. In addition, the threshold temperature of the vector involved in the calculations was 12.17°C, while the accumulated day-degree (DD) had to exceed the annual and biennial 370.57°DD for univoltine and semivoltine development, respectively. Our finding that a connection could be found between a mean temperature in July above 20°C and NAO as well as between the accumulated day-degrees and NAO can be the basis for further investigations for a reliable method to forecast the expansion of pine wood nematode and its vector species in a given year.