scholarly journals Swarm Robot Exploration Strategy for Path Formation Tasks Inspired by Physarum polycephalum

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yandong Luo ◽  
Jianwen Guo ◽  
Zhenpeng Lao ◽  
Shaohui Zhang ◽  
Xiaohui Yan
Keyword(s):  
Physarum Polycephalum ◽  
Food Sources ◽  
Multirobot Systems ◽  
Adaptive Networks ◽  
Navigation Strategy ◽  
Swarm Robots ◽  
Distant Target ◽  
Swarm Robot ◽  
Efficient Exploration ◽  
The Individual

Physarum polycephalum, a unicellular and multiheaded slime mould, can form highly efficient networks connecting separated food sources during the process of foraging. These adaptive networks exhibit a unique characteristic in that they are optimized without the control of a central consciousness. Inspired by this phenomenon, we present an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to overcome the limited abilities of the individual robots. The task faced by the robots consists in the exploration of an unknown environment in order to find a path between two distant target areas. For the proposed algorithm (EAIPP), we experimentally present robustness tests and obstacle tests conducted to analyse the performance of our algorithm and compare the proposed algorithm with other swarm robot foraging algorithms that also focus on the path formation task. This work has certain significance for the research of swarm robots and Physarum polycephalum. For the research of swarm robotics, our algorithm not only can lead multirobot as a whole to overcome the limitations of very simple individual agents but also can offer better performance in terms of search efficiency and success rate. For the research of Physarum polycephalum, this work is the first one combining swarm robots and Physarum polycephalum. It also reveals the potential of the Physarum polycephalum foraging principle in multirobot systems.

Sharing Experience for Behavior Generation of Real Swarm Robot Systems Using Deep Reinforcement Learning

2019 ◽  
Vol 31 (4) ◽  
pp. 520-525 ◽  
Author(s):  
Toshiyuki Yasuda ◽  
Kazuhiro Ohkura ◽  
◽  
Keyword(s):  
Reinforcement Learning ◽  
Collective Behavior ◽  
Design Methodology ◽  
Learning Performance ◽  
Centralized Control ◽  
Robot System ◽  
Swarm Robots ◽  
Robot Systems ◽  
Swarm Robot ◽  
Typical Design

Swarm robotic systems (SRSs) are a type of multi-robot system in which robots operate without any form of centralized control. The typical design methodology for SRSs comprises a behavior-based approach, where the desired collective behavior is obtained manually by designing the behavior of individual robots in advance. In contrast, in an automatic design approach, a certain general methodology is adopted. This paper presents a deep reinforcement learning approach for collective behavior acquisition of SRSs. The swarm robots are expected to collect information in parallel and share their experience for accelerating their learning. We conducted real swarm robot experiments and evaluated the learning performance of the swarm in a scenario where the robots consecutively traveled between two landmarks.

scholarly journals Do city cachers store less? The effect of urbanization and exploration on spatial memory in individual scatter hoarders

2018 ◽  
Author(s):  
Megan Joy Thompson ◽  
Julie Morand-Ferron
Keyword(s):  
Spatial Memory ◽  
Spatial Task ◽  
Food Sources ◽  
Urban Gradient ◽  
Supplemental Food ◽  
Rural Environments ◽  
Bird Feeders ◽  
The Individual ◽  
Speed Accuracy ◽  
First Time

Urbanization has been shown to affect a variety of traits in animals, including their physiology, morphology, and behaviour, but it is less clear how cognitive traits are modified. Urban habitats contain artificially elevated food sources, such as bird feeders, that are known to affect the foraging behaviours of urban animals. As of yet however, it is not known whether urbanization and the abundance of supplemental food during the winter reduce caching behaviours and spatial memory in scatter hoarders. We aimed to examine individual variation in caching and spatial memory between and within urban and rural habitats to determine i) whether urban individuals cache less frequently and perform less accurately on a spatial task, and ii) explore, for the first time in scatter hoarders, whether slower explorers perform more accurately on a spatial task, indicating a speed-accuracy trade-off within individuals. We assessed spatial memory of wild-caught black-capped chickadees (Poecile atricapillus; N = 96) from 14 sites along an urban gradient. While the individuals that cached more food in captivity were all from rural environments, we find no clear evidence that caching intensity and spatial memory accuracy differ along an urban gradient, and find no significant relationship between spatial cognition and exploration of a novel environment within individuals. However, individuals that performed more accurately also tended to cache more frequently, suggesting for the first time that the specialization of spatial memory in scatter hoarders may also occur at the level of the individual in addition to the population and species levels.

scholarly journals Artificial selection for predatory behavior results in dietary niche differentiation in an omnivorous mammal

2021 ◽  
Author(s):  
Anni M Hämäläinen ◽  
Mikko Kiljunen ◽  
Esa Koskela ◽  
Pawel Koteja ◽  
Tapio Mappes ◽  
...  
Keyword(s):  
Late Summer ◽  
Niche Differentiation ◽  
Predatory Behavior ◽  
Early Summer ◽  
Food Sources ◽  
Diet Choice ◽  
Behavioral Selection ◽  
Plant Matter ◽  
Dietary Niche ◽  
The Individual

The diet of an individual is a result of the availability of dietary items and the individual's foraging skills and preferences. Behavioral differences may thus influence diet variation, but the evolvability of diet choice through behavioral evolution has not been studied. We used experimental evolution combined with a field enclosure experiment to test whether behavioral selection leads to dietary divergence. We analysed the individual dietary niche via stable isotope ratios of nitrogen (δ15N) and carbon (δ13C) in the hair of an omnivorous mammal, bank vole, from 4 lines selected for predatory behavior and 4 unselected control lines. Predatory voles had higher hair δ15N values than control voles, supporting our hypothesis that predatory voles would consume a higher trophic level diet (more animal vs. plant foods). This difference was significant in the early but not the late summer season. The δ13C values also indicated a seasonal change in the consumed plant matter and a difference in food sources among selection lines in the early summer. These results imply that environmental factors interact with evolved behavioral tendencies to determine dietary niche heterogeneity. Behavioral selection thus has potential to contribute to the evolution of diet choice and ultimately the species' ecological niche breadth.

scholarly journals Vultures and Livestock: The Where, When, and Why of Visits to Farms

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2127
Author(s):  
Marina García-Alfonso ◽  
Thijs van Overveld ◽  
Laura Gangoso ◽  
David Serrano ◽  
José A. Donázar
Keyword(s):  
Population Structure ◽  
Spatial Distribution ◽  
Breeding Season ◽  
Individual Characteristics ◽  
Food Sources ◽  
Core Areas ◽  
Vulture Conservation ◽  
Using Data ◽  
The Individual ◽  
Feeding Resources

Recent changes in European legislation have legalized the abandonment of carcasses around livestock farms, but our understanding of how vultures exploit these semi-predictable food sources is still very limited. For filling this gap, we determine the individual and ecological drivers influencing vulture visits to farms. We assessed the effects of individual characteristics of both birds and farms on the frequency of vultures’ visits to livestock facilities using data collected from 45 GPS-tagged Egyptian Vultures (Neophron percnopterus) and 318 farms (>94% of livestock) on Fuerteventura Island, Spain. Farms were more visited during the vultures’ breeding season. Farms located closer to highly predictable feeding places (i.e., vulture restaurants and garbage dumps) or with more available feeding resources were visited by more vultures, whereas those located close to roads and vultures’ breeding territories received fewer visits. Younger territorial birds visited a farm more frequently than older territorial ones, whereas older non-territorial individuals concentrated those visits on farms closer to their activity core areas compared with younger ones. Our findings indicate that visits to farms were determined by their spatial distribution in relation to the age-specific birds’ activity centers, the availability of carcasses, seasonality, and individual characteristics of vultures. These interacting factors should be considered in vulture conservation, avoiding very general solutions that ignore population structure.

COMMITTEE ON NUTRITION

PEDIATRICS ◽  
1963 ◽  
Vol 31 (3) ◽  
pp. 512-525
Author(s):  
Keyword(s):  
Vitamin D ◽  
Young Infant ◽  
Age Groups ◽  
The United States ◽  
Food Sources ◽  
Older Children ◽  
Normal Children ◽  
Vitamin D Supplements ◽  
The Individual ◽  
Daily Intakes

Despite inadequacies in information concerning the minimum prophylactic requirement of vitamin D for all age groups beyond infancy, there is no doubt that a total intake of 400 I.U. per day is adequate to prevent vitamin D deficiency in substantially all normal children from birth through adolescence. Evidence derived from the study of idiopathic hypercalcemia suggests that certain infants excessively sensitive to the toxic action of vitamin D may, on rare occasions, be adversely affected by daily intakes of 3,000 to 4,000 I.U. and sometimes considerably less. Because of the prevalent practice of food fortification in the United States and Canada, there is now a definite possibility that the individual, even the young infant, may ingest considerably more than the recommended vitamin D allowance, and intakes of 2,000 to 3,500 I.U. per day are possible, particularly beyond infancy. Although there has been no specific evidence that intakes of this order produce deleterious effects beyond infancy, it is pointed out that the long-term consequences of this new nutritional situation on older children or adults are entirely unknown. In view of these considerations the Committee on Nutrition recommends that efforts be taken to ensure a total vitamin D intake of 400 I.U. per day by all infants and children. At the same time, an attempt should be made to restrict the intake from all sources to an amount not greatly in excess of this figure. The value of carefully planned enrichment of commercial milk supplies with vitamin D has been clearly demonstrated. However, the present practice of enriching foods other than milk and infant formula products is not justified, and discontinuation of this practice is to be recommended. Under the present circumstances, cognizance should be taken of the amount of vitamin D acquired by the individual from food sources before prescribing a vitamin D supplement. In keeping with present concepts regarding vitamin D requirement, commercial vitamin D supplements should be adjusted to contain not more than 400 I.U. per dose.

Multi Robot Exploration through Pruning Frontiers

2012 ◽  
Vol 462 ◽  
pp. 609-616 ◽  
Author(s):  
Anshika Pal ◽  
Ritu Tiwari ◽  
Anupam Shukla
Keyword(s):  
Open Space ◽  
Clustering Algorithm ◽  
Unsupervised Clustering ◽  
Search And Rescue ◽  
Computational Time ◽  
Navigation Strategy ◽  
Key Issues ◽  
The Individual ◽  
Target Locations ◽  
Multi Robot

In this paper, an approach to multi robot exploration is presented. One of the key issues in multi robot exploration is how to assign target locations to the individual robots and how to better distribute the robots over the environment. The proposed technique applies a well-known unsupervised clustering algorithm (k-means) in order to fairly divide the space into as many disjoint regions as available robots. Hungarian Method is used for the assignment of robots to the individual regions with the task to explore the corresponding area. To drive the robots around the environment, a frontier ‘regions on the boundary between open space and unexplored space’ based navigation strategy is used to decide where to move next, according to the data collected so far. Furthermore, we discuss improvements to the frontier based exploration strategy, by pruning the frontier cells that further reduces the computational time. The numbers of candidate locations are evaluated based on three criteria: number of unknown cells, number of known cells and real path travelling cost. Simulations are presented to show the performance of the proposed technique. This method can best be applied in search and rescue operations, partitioning helps to explore different regions of the workspace parallely by different robots instead of concentrating efforts in particular spot, pruning helps to make movement decisions much faster, the result is that the potential victims in a region will not have to wait much longer.

scholarly journals Behavior-Based Formation Control of Swarm Robots

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Dongdong Xu ◽  
Xingnan Zhang ◽  
Zhangqing Zhu ◽  
Chunlin Chen ◽  
Pei Yang
Keyword(s):  
Formation Control ◽  
Large Scale ◽  
Research Field ◽  
Initial Formation ◽  
Swarm Robots ◽  
Robot Systems ◽  
Potential Applications ◽  
Behavior Based ◽  
Swarm Robot ◽  
Searching Method

Swarm robotics is a specific research field of multirobotics where a large number of mobile robots are controlled in a coordinated way. Formation control is one of the most challenging goals for the coordination control of swarm robots. In this paper, a behavior-based control design approach is proposed for two kinds of important formation control problems: efficient initial formation and formation control while avoiding obstacles. In this approach, a classification-based searching method for generating large-scale robot formation is presented to reduce the computational complexity and speed up the initial formation process for any desired formation. The behavior-based method is applied for the formation control of swarm robot systems while navigating in an unknown environment with obstacles. Several groups of experimental results demonstrate the success of the proposed approach. These methods have potential applications for various swarm robot systems in both the simulation and the practical environments.

scholarly journals Sociability increases survival of adult female giraffes

2021 ◽  
Vol 288 (1944) ◽  
pp. 20202770
Author(s):  
M. L. Bond ◽  
D. E. Lee ◽  
D. R. Farine ◽  
A. Ozgul ◽  
B. König
Keyword(s):  
Environmental Factors ◽  
Adult Female ◽  
Social Connectedness ◽  
Group Membership ◽  
Demographic Data ◽  
Food Sources ◽  
Adult Survival ◽  
Natural Food ◽  
Social Traits ◽  
The Individual

Studies increasingly show that social connectedness plays a key role in determining survival, in addition to natural and anthropogenic environmental factors. Few studies, however, integrated social, non-social and demographic data to elucidate what components of an animal's socio-ecological environment are most important to their survival. Female giraffes ( Giraffa camelopardalis ) form structured societies with highly dynamic group membership but stable long-term associations. We examined the relative contributions of sociability (relationship strength, gregariousness and betweenness), together with those of the natural (food sources and vegetation types) and anthropogenic environment (distance from human settlements), to adult female giraffe survival. We tested predictions about the influence of sociability and natural and human factors at two social levels: the individual and the social community. Survival was primarily driven by individual- rather than community-level social factors. Gregariousness (the number of other females each individual was observed with on average) was most important in explaining variation in female adult survival, more than other social traits and any natural or anthropogenic environmental factors. For adult female giraffes, grouping with more other females, even as group membership frequently changes, is correlated with better survival, and this sociability appears to be more important than several attributes of their non-social environment.

scholarly journals Multi-Target Coordinated Search Algorithm for Swarm Robotics Considering Practical Constraints

2021 ◽  
Vol 15 ◽  
Author(s):  
You Zhou ◽  
Anhua Chen ◽  
Xinjie He ◽  
Xiaohui Bian
Keyword(s):  
Obstacle Avoidance ◽  
Search Algorithm ◽  
Robot Kinematics ◽  
Force Model ◽  
Target Search ◽  
Random Line ◽  
Swarm Robots ◽  
Distributed Communication ◽  
Swarm Robot ◽  
Practical Constraints

In order to deal with the multi-target search problems for swarm robots in unknown complex environments, a multi-target coordinated search algorithm for swarm robots considering practical constraints is proposed in this paper. Firstly, according to the target detection situation of swarm robots, an ideal search algorithm framework combining the strategy of roaming search and coordinated search is established. Secondly, based on the framework of the multi-target search algorithm, a simplified virtual force model is combined, which effectively overcomes the real-time obstacle avoidance problem in the target search of swarm robots. Finally, in order to solve the distributed communication problem in the multi-target search of swarm robots, a distributed neighborhood communication mechanism based on a time-varying characteristic swarm with a restricted random line of sight is proposed, and which is combined with the multi-target search framework. For the swarm robot kinematics, obstacle avoidance, and communication constraints of swarm robots, the proposed multi-target search strategy is more stable, efficient, and practical than the previous methods. The effectiveness of this proposed method is verified by numerical simulations.

Research on the Optimization Scheme of Base Station Construction Based on Artificial Bee Colony Algorithm

2014 ◽  
Vol 602-605 ◽  
pp. 3612-3615
Author(s):  
Wei Ping Wang ◽  
Miao Yang ◽  
Tao Li ◽  
Ying Qin
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimal Solution ◽  
Base Station ◽  
Food Sources ◽  
Mobile Service ◽  
Construction Costs ◽  
Bee Colony ◽  
Construction Scheme ◽  
The Individual

Artificial bee colony algorithm is a new meta heuristic bionic algorithm.Each bee can be viewed as an agent in the algorithm.Through the swarm synergies between the individual achieve the effect of swarm intelligence.Based on the analysis on the principle of bees gather honey,the process of solving functional optimization is converted into the process of swarm finding rich food sources,then we can solve the function.With the arrival of 4G Era,Base station construction is the most crucial step of the mobile communication network popularization, its significance and role should not be underestimated.How to realize the optimization of communication base station construction costs has been the research focus of the mobile service operator and colleges and universities.The artificial bee colony algorithm is applied to solve the optimal solution of base station construction scheme in this paper,which is very critical reference for decision in real base station construction.

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