Autonomous Trail Following

2017 ◽  
Author(s):  
Masoud Hoveidar-Sefid ◽  
Michael Jenkin
Keyword(s):  
Trail Following

Synthetic analogues of the termite trail-following pheromone, structure and biological activity

1971 ◽  
Vol 17 (1) ◽  
pp. 181-188 ◽  
Author(s):  
Akira Tai ◽  
F. Matsumura ◽  
H.C. Coppel
Keyword(s):  
Biological Activity ◽  
Trail Following ◽  
Synthetic Analogues

Directionality in the trail‐following response of the pulmonate limpet Siphonaria alternata

1975 ◽  
Vol 3 (3) ◽  
pp. 147-155 ◽  
Author(s):  
Susan Blackford Cook ◽  
Clayton B. Cook
Keyword(s):  
Trail Following

scholarly journals Trail-following behaviour in two Aphaenogaster ants

Chemoecology ◽  
2011 ◽  
Vol 21 (2) ◽  
pp. 83-88 ◽  
Author(s):  
Alain Lenoir ◽  
Amélie Benoist ◽  
Abraham Hefetz ◽  
Wittko Francke ◽  
Xim Cerdá ◽  
...  
Keyword(s):  
Trail Following

Structure-activity relationships among aromatic analogs of trail-following pheromone of subterranean termites

1984 ◽  
Vol 10 (8) ◽  
pp. 1201-1217 ◽  
Author(s):  
Glenn D. Prestwich ◽  
Wai -Si Eng ◽  
Ellen Deaton ◽  
David Wichern
Keyword(s):  
Subterranean Termites ◽  
Trail Following ◽  
Structure Activity Relationships ◽  
Structure Activity

scholarly journals Sensor Fusion-Based Cooperative Trail Following for Autonomous Multi-Robot System

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 823 ◽  
Author(s):  
Mingyang Geng ◽  
Shuqi Liu ◽  
Zhaoxia Wu
Keyword(s):  
Sensor Fusion ◽  
Sensor Data ◽  
Great Success ◽  
Trail Following ◽  
Robust Performance ◽  
Robot System ◽  
Threshold Mechanism ◽  
Local View ◽  
In The Wild

Autonomously following a man-made trail in the wild is a challenging problem for robotic systems. Recently, deep learning-based approaches have cast the trail following problem as an image classification task and have achieved great success in the vision-based trail-following problem. However, the existing research only focuses on the trail-following task with a single-robot system. In contrast, many robotic tasks in reality, such as search and rescue, are conducted by a group of robots. While these robots are grouped to move in the wild, they can cooperate to lead to a more robust performance and perform the trail-following task in a better manner. Concretely, each robot can periodically exchange the vision data with other robots and make decisions based both on its local view and the information from others. This paper proposes a sensor fusion-based cooperative trail-following method, which enables a group of robots to implement the trail-following task by fusing the sensor data of each robot. Our method allows each robot to face the same direction from different altitudes to fuse the vision data feature on the collective level and then take action respectively. Besides, considering the quality of service requirement of the robotic software, our method limits the condition to implementing the sensor data fusion process by using the “threshold” mechanism. Qualitative and quantitative experiments on the real-world dataset have shown that our method can significantly promote the recognition accuracy and lead to a more robust performance compared with the single-robot system.

scholarly journals Ants Sense, and Follow, Trail Pheromones of Ant Community Members

Insects ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 383 ◽  
Author(s):  
Jaime M. Chalissery ◽  
Asim Renyard ◽  
Regine Gries ◽  
Danielle Hoefele ◽  
Santosh Kumar Alamsetti ◽  
...  
Keyword(s):  
Trail Pheromone ◽  
Food Sources ◽  
Lasius Niger ◽  
Trail Following ◽  
Harvester Ants ◽  
Community Members ◽  
Trail Pheromones ◽  
Ant Community ◽  
Carpenter Ants ◽  
Electroantennographic Detection

Ants deposit trail pheromones that guide nestmates to food sources. We tested the hypotheses that ant community members (Western carpenter ants, Camponotus modoc; black garden ants, Lasius niger; European fire ants, Myrmica rubra) (1) sense, and follow, each other’s trail pheromones, and (2) fail to recognize trail pheromones of allopatric ants (pavement ants, Tetramorium caespitum; desert harvester ants, Novomessor albisetosus; Argentine ants, Linepithema humilis). In gas chromatographic-electroantennographic detection analyses of a six-species synthetic trail pheromone blend (6-TPB), La. niger, Ca. modoc, and M. rubra sensed the trail pheromones of all community members and unexpectedly that of T. caespitum. Except for La. niger, all species did not recognize the trail pheromones of N. albisetosus and Li. humilis. In bioassays, La. niger workers followed the 6-TPB trail for longer distances than their own trail pheromone, indicating an additive effect of con- and hetero-specific pheromones on trail-following. Moreover, Ca. modoc workers followed the 6-TPB and their own trail pheromones for similar distances, indicating no adverse effects of heterospecific pheromones on trail-following. Our data show that ant community members eavesdrop on each other’s trail pheromones, and that multiple pheromones can be combined in a lure that guides multiple species of pest ants to lethal food baits.

scholarly journals Substrate Temperature Constrains Recruitment and Trail Following Behavior in Ants

2012 ◽  
Vol 38 (6) ◽  
pp. 802-809 ◽  
Author(s):  
Louise van Oudenhove ◽  
Raphaël Boulay ◽  
Alain Lenoir ◽  
Carlos Bernstein ◽  
Xim Cerda
Keyword(s):  
Substrate Temperature ◽  
Trail Following
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