Robot navigation

Robot navigation using visual and sensorimotor information (2013)

Robot localizationdenotes the robot's ability to establish its own position and orientation within theframe of reference.Path planningis effectively an extension of localization, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference.^{[citation needed]}

For any mobile device, the ability to navigate in its environment is important. Avoiding dangerous situations such as collisions and unsafe conditions (temperature,radiation, exposure to weather, etc.) comes first, but if the robot has a purpose that relates to specific places in the robot environment, it must find those places. This article will present an overview of the skill of navigation and try to identify the basic blocks of a robotnavigation system,types of navigation systems, and closer look at its related building components.

Robot navigation means the robot's ability to determine its own position in itsframe of referenceand then to plan a path towards some goal location. In order to navigate in its environment, the robot or any other mobility device requires representation, i.e. a map of the environment and the ability tointerpretthat representation.

Navigation can be defined as the combination of the three fundamental competences:^[1]

Self-localization
Path planning
Map-buildingand map interpretation

Some robot navigation systems usesimultaneous localization and mappingto generate3D reconstructionsof their surroundings.^[2]

Vision-based navigation[edit]

Vision-based navigation or optical navigation usescomputer visionalgorithms and optical sensors, including laser-basedrange finderand photometric cameras usingCCDarrays, to extract thevisual featuresrequired to the localization in the surrounding environment. However, there are a range of techniques for navigation and localization using vision information, the main components of each technique are:

representations of the environment.
sensing models.
localization algorithms.

In order to give an overview of vision-based navigation and its techniques, we classify these techniques underindoor navigationandoutdoor navigation.

Indoor navigation[edit]

Egomotion estimationfrom a moving camera

The easiest way of making a robot go to a goal location is simply toguideit to this location. This guidance can be done in different ways: burying an inductive loop or magnets in the floor, painting lines on the floor, or by placing beacons, markers, bar codes etc. in the environment. SuchAutomated Guided Vehicles(AGVs)are used in industrial scenarios for transportation tasks. Indoor Navigation of Robots are possible by IMU based indoor positioning devices.^[3]^[4]

There are a very wider variety of indoor navigation systems. The basic reference of indoor and outdoor navigation systems is"Vision for mobile robot navigation: a survey"by Guilherme N. DeSouza and Avinash C. Kak.

Also see"Vision based positioning"andAVM Navigator.

Autonomous Flight Controllers[edit]

Typical Open Source Autonomous Flight Controllers have the ability to fly in full automatic mode and perform the following operations;

Take off from the ground and fly to a defined altitude
Fly to one or more waypoints
Orbit around a designated point
Return to the launch position
Descend at a specified speed and land the aircraft

The onboard flight controller relies on GPS for navigation and stabilized flight, and often employ additionalSatellite-based augmentation systems(SBAS) and altitude (barometric pressure) sensor.^[5]

Inertial navigation[edit]

Some navigation systems for airborne robots are based oninertial sensors.^[6]

Acoustic navigation[edit]

Autonomous underwater vehiclescan be guided byunderwater acoustic positioning systems.^[7]Navigation systems usingsonarhave also been developed.^[8]

Radio navigation[edit]

Robots can also determine their positions usingradio navigation.^[9]

References[edit]

^Stachniss, Cyrill. "Robotic mapping and exploration."Vol. 55. Springer, 2009.
^Fuentes-Pacheco, Jorge, José Ruiz-Ascencio, and Juan Manuel Rendón-Mancha. "Visual simultaneous localization and mapping: a survey."Artificial Intelligence Review 43.1 (2015): 55-81.
^Chen, C.; Chai, W.; Nasir, A. K.; Roth, H. (April 2012). "Low cost IMU based indoor mobile robot navigation with the assist of odometry and Wi-Fi using dynamic constraints".Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.pp. 1274–1279.doi:10.1109/PLANS.2012.6236984.ISBN 978-1-4673-0387-3.S2CID 19472012.
^GT Silicon (2017-01-07),An awesome robot with cool navigation and real-time monitoring,archivedfrom the original on 2021-12-12,retrieved2018-04-04
^"Flying | AutoQuad".
^Bruno Siciliano; Oussama Khatib (20 May 2008).Springer Handbook of Robotics.Springer Science & Business Media. pp. 1020–.ISBN 978-3-540-23957-4.
^Mae L. Seto (9 December 2012).Marine Robot Autonomy.Springer Science & Business Media. pp. 35–.ISBN 978-1-4614-5659-9.
^John J. Leonard; Hugh F. Durrant-Whyte (6 December 2012).Directed Sonar Sensing for Mobile Robot Navigation.Springer Science & Business Media.ISBN 978-1-4615-3652-9.
^Oleg Sergiyenko (2019).Machine Vision and Navigation.Springer Nature. pp. 172–.ISBN 978-3-030-22587-2.

External links[edit]

line tracking sensors for robots and its algorithms

[1] Stachniss, Cyrill. "Robotic mapping and exploration."Vol. 55. Springer, 2009.

[2] Fuentes-Pacheco, Jorge, José Ruiz-Ascencio, and Juan Manuel Rendón-Mancha. "Visual simultaneous localization and mapping: a survey."Artificial Intelligence Review 43.1 (2015): 55-81.

[3] Chen, C.; Chai, W.; Nasir, A. K.; Roth, H. (April 2012). "Low cost IMU based indoor mobile robot navigation with the assist of odometry and Wi-Fi using dynamic constraints".Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.pp. 1274–1279.doi:10.1109/PLANS.2012.6236984.ISBN 978-1-4673-0387-3.S2CID 19472012.

[4] GT Silicon (2017-01-07),An awesome robot with cool navigation and real-time monitoring,archivedfrom the original on 2021-12-12,retrieved2018-04-04

[5] "Flying | AutoQuad".

[SicilianoKhatib2008-6] Bruno Siciliano; Oussama Khatib (20 May 2008).Springer Handbook of Robotics.Springer Science & Business Media. pp. 1020–.ISBN 978-3-540-23957-4.

[Seto2012-7] Mae L. Seto (9 December 2012).Marine Robot Autonomy.Springer Science & Business Media. pp. 35–.ISBN 978-1-4614-5659-9.

[LeonardDurrant-Whyte2012-8] John J. Leonard; Hugh F. Durrant-Whyte (6 December 2012).Directed Sonar Sensing for Mobile Robot Navigation.Springer Science & Business Media.ISBN 978-1-4615-3652-9.

[Sergiyenko-9] Oleg Sergiyenko (2019).Machine Vision and Navigation.Springer Nature. pp. 172–.ISBN 978-3-030-22587-2.

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