Navigation in desert ants: the robotic solution

The desert ant Cataglyphis is able to explore its desert habitat for hundreds of meters while foraging and return back to its nest precisely and in a straight line. With a body of less than 10 mm and a brain of less than one cubic millimeter they provide a challenge for hi-tech engineers. In this article, we give an overview of our attempts to model parts of its navigation behavior using robots and computer simulations. Inspired by the insect's navigation system we have developed mechanisms for path integration and visual piloting that were successfully employed on the mobile robot Sahabot 2.

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Flexible weighing of olfactory and vector information in the desert ant Cataglyphis fortis

Biology Letters ◽

10.1098/rsbl.2013.0070 ◽

2013 ◽

Vol 9 (3) ◽

pp. 20130070 ◽

Cited By ~ 10

Author(s):

Cornelia Buehlmann ◽

Bill S. Hansson ◽

Markus Knaden

Keyword(s):

Path Integration ◽

Food Sources ◽

Feeding Site ◽

Desert Ants ◽

Desert Ant ◽

Vector Information ◽

Pass Through ◽

Path Integrator ◽

Odour Plumes ◽

Cataglyphis Fortis

Desert ants, Cataglyphis fortis , are equipped with remarkable skills that enable them to navigate efficiently. When travelling between the nest and a previously visited feeding site, they perform path integration (PI), but pinpoint the nest or feeder by following odour plumes. Homing ants respond to nest plumes only when the path integrator indicates that they are near home. This is crucial, as homing ants often pass through plumes emanating from foreign nests and do not discriminate between the plume of their own and that of a foreign nest, but should absolutely avoid entering a wrong nest. Their behaviour towards food odours differs greatly. Here, we show that in ants on the way to food, olfactory information outweighs PI information. Although PI guides ants back to a learned feeder, the ants respond to food odours independently of whether or not they are close to the learned feeding site. This ability is beneficial, as new food sources—unlike foreign nests—never pose a threat but enable ants to shorten distances travelled while foraging. While it has been shown that navigating C. fortis ants rely strongly on PI, we report here that the ants retained the necessary flexibility in the use of PI.

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INFORMATION ACQUISITION IN DESERT ANT NAVIGATION

International Journal of Information Acquisition ◽

10.1142/s0219878906000800 ◽

2006 ◽

Vol 03 (01) ◽

pp. 33-43 ◽

Cited By ~ 3

Author(s):

JUN GAO ◽

LEI WANG ◽

MEI BO ◽

ZHIGUO FAN

Keyword(s):

Body Length ◽

Information Acquisition ◽

Path Integration ◽

Research Work ◽

Polarized Light ◽

Visual Navigation ◽

Desert Ant ◽

Navigation Path ◽

Straight Line ◽

Ant Navigation

Desert ant (Cataglyphis) is famous for its ability in navigation. In deserts with very few visual and odor information, the ant can return to its den almost along a straight line after foraging away in a distance of much more than thousands of times longer than its body length. Several kinds of information must be acquired during its trip, and the most important two are: path integration and visual navigation. Path integration is achieved by using sky light compass based on polarized light and odometer, while visual navigation relies on landmark based memory and matching. In this paper, a survey of research work on desert ant navigation from the viewpoint of information acquisition and fusion is presented, as well as the application of these kinds of information to navigate robots, especially bionic robots cruising in strange environment.

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Indoor Navigation System of Omni-Directional Mobile Robot Based on Static Obstacles Avoidance

International Review of Automatic Control (IREACO) ◽

10.15866/ireaco.v13i1.18346 ◽

2020 ◽

Vol 13 (1) ◽

pp. 27

Author(s):

Shaaban Ali Salman ◽

Qais A. Khasawneh ◽

Mohammad A. Jaradat ◽

Mansour Y. Alramlawi

Keyword(s):

Mobile Robot ◽

Navigation System ◽

Indoor Navigation ◽

Indoor Navigation System

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Smart and Fully Functional Mobile-Robot Navigation System

2021 7th International Conference on Control, Automation and Robotics (ICCAR) ◽

10.1109/iccar52225.2021.9463451 ◽

2021 ◽

Author(s):

Mohammed Faisal ◽

Mohammed Algabri ◽

Mohamed Amine Mekhtiche

Keyword(s):

Mobile Robot ◽

Navigation System ◽

Robot Navigation ◽

Mobile Robot Navigation

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A novel navigation system for an autonomous mobile robot in an uncertain environment

Robotica ◽

10.1017/s0263574721000497 ◽

2021 ◽

pp. 1-26

Author(s):

Meng-Yuan Chen ◽

Yong-Jian Wu ◽

Hongmei He

Keyword(s):

Mobile Robot ◽

Navigation System ◽

Autonomous Navigation ◽

Clustering Algorithm ◽

Modular Design ◽

Optimal Path ◽

Surrounding Environment ◽

Computing Complexity ◽

The Arts ◽

Window Approach

Abstract In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.

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