Self-organized search-attack mission planning for UAV swarm based on wolf pack hunting behavior

Cooperative search-attack is an important application of unmanned aerial vehicle(UAV)swarm in military field.The coupling between path planning and task allocation,the heterogeneity of UAVs,and the dynamic nature of task environment greatly increase the complexity and difficulty of the UAV swarm cooperative search-attack mission planning problem.Inspired by the collaborative hunting behavior of wolf pack,a distributed selforganizing method for UAV swarm search-attack mission planning is proposed.First,to solve the multi-target search problem in unknown environments,a wolf scouting behavior-inspired cooperative search algorithm for UAV swarm is designed.Second,a distributed self-organizing task allocation algorithm for UAV swarm cooperative attacking of targets is proposed by analyzing the flexible labor division behavior of wolves.By abstracting the UAV as a simple artificial wolf agent,the flexible motion planning and group task coordinating for UAV swarm can be realized by self-organizing.The effectiveness of the proposed method is verified by a set of simulation experiments,the stability and scalability are evaluated,and the integrated solution for the coupled path planning and task allocation problems for the UAV swarm cooperative search-attack task can be well performed.

First evidence of prey capture and meat eating by wild Yunnan snub-nosed monkeys Rhinopithecus bieti in Yunnan,China

Most extant nonhuman primates occasionally prey on fast-moving, warm-blooded animals; however, Indriidae, Lepilemuridae, and Colobinae either scavenged for meat or did not eat meat at all. Here we report six cases of animal consumption by the snub-nosed monkey Rhinopithecus bieti in a wild, habituated group between 2004 and 2009 in Yunnan, China. At present, only males in an all-male unit within the study group were involved in active hunting. Such a male-biased activity may be related to the group structure and spatial spread of R. bieti. Two females were observed eating freshly killed birds. The findings confirmed that R. bieti engaged in scavenging and, when hunting, employed a cranio-cervical bite to kill their prey. Meat eating is likely a nutrient maximization feeding strategy in R. bieti, especially in males. A begging behavior occurred after successful prey capture. Although begging was observed, no sharing of the meat was seen. The present findings illuminate the dietary diversity of R. bieti and their ability to expand their dietary spectrum.

Stochastic rules for predator and prey hunting and escape behavior in a lattice-based model

Understanding of ecosystem resilience and stability requires comprehending predator- prey dynamics because ecosystems consist of dynamically interacting subsystems that include predator-prey relationships. This relationship is closely related to the hunting- escaping strategies employed by the predator and prey. Therefore, understanding the effects of hunting and escaping strategies on ecosystems will lead to a better under- standing of these systems. As an approach for describing the predator-prey interaction, lattice-based models have been adopted because this approach has strong advantages for simulating various dynamical processes of individual-individual interaction. In the models, each lattice cell is either considered as an attractive/repulsive cell, or an indi- vidual cell, or else it is empty. The attractive （or repulsive cell） can be interpreted as the prey （or predator） of the individual. These states allow us to incorporate the ecological processes of local antagonistic interactions, namely the spread of disturbances （by the predator） and regrowth or recovery （by the prey）. These processes are directly related to the strategic behavior of individuals, such as hunting and escaping. In this study, we suggest a simple and effective mapping formula as a stochastic rule to describe the hunt- ing and escaping behavior. This formula could be widely used not only in the behavior but also in competitive and cooperative relationships.