Hippocampal formation-inspired global self-localization: quick recovery from the kidnapped robot problem from an egocentric perspective

Autor: Takeshi Nakashima, Shunsuke Otake, Akira Taniguchi, Katsuyoshi Maeyama, Lotfi El Hafi, Tadahiro Taniguchi, Hiroshi Yamakawa

Publikováno v: Frontiers in Computational Neuroscience, Vol 18 (2024)

It remains difficult for mobile robots to continue accurate self-localization when they are suddenly teleported to a location that is different from their beliefs during navigation. Incorporating insights from neuroscience into developing a spatial c

Externí odkaz: https://doaj.org/article/2ea59904489a4f038ee08423bbe0fb63

Canopy-Based Monte Carlo Localization in Orchards Using Top-View Imagery

Autor: Omer Shalev, Amir Degani

Publikováno v: IEEE Robotics and Automation Letters. 5:2403-2410

Localization of ground mobile robots in orchards is a complex problem which is yet to be fully addressed. The typical localization approaches are not adjusted to the characteristics of the orchard environment, especially the homogeneous scenery. To a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ac69fa12dbdad4f6e7f472ce9f52528b
https://doi.org/10.1109/lra.2020.2970975

Robust Hybrid Interval-Probabilistic Approach for the Kidnapped Robot Problem

Autor: Mathias Mantelli, Renata Neuland, Edson Prestes, Mariana Kolberg, Bernardo Hummes, Luc Jaulin, Renan Maffei

Publikováno v: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific Publishing, 2021, 29 (02), pp.313-331. ⟨10.1142/S0218488521500141⟩

International audience; For a mobile robot to operate in its environment it is crucial to determine its position with respect to an external reference frame using noisy sensor readings. A scenario in which the robot is moved to another position durin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b64486b86c6e2a02f575a999bb9fa25
https://hal-ensta-bretagne.archives-ouvertes.fr/hal-03254742

Improved Global Localization and Resampling Techniques for Monte Carlo Localization Algorithm

Autor: Hasan Ocak, Humam Abualkebash

Publikováno v: Volume: 8, Issue: 3 102-108
International Journal of Applied Mathematics Electronics and Computers

Global indoor localization algorithms enable the robot to estimate its pose in pre-mapped environments using sensor measurements when its initial pose is unknown. The conventional Adaptive Monte Carlo Localization (AMCL) is a highly efficient localiz

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::817b3a5ae0b38517b63ec46cefb34d8e
https://dergipark.org.tr/tr/pub/ijamec/issue/56999/800166

Cost-effective Indoor Localization for Autonomous Robots using Kinect and WiFi Sensors

Autor: Josué Silva de Morais, Keiji Yamanaka, Raul Cesar Alves

Publikováno v: Inteligencia Artificial, Vol 23, Iss 65 (2020)

Indoor localization has been considered to be the most fundamental problem when it comes to providing a robot with autonomous capabilities. Although many algorithms and sensors have been proposed, none have proven to work perfectly under all situatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::786fdc654c428064fa03b45e678a1542
https://journal.iberamia.org/index.php/intartif/article/view/345