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Application of the MyRIO Based Mobile Robot Using Vision System
Ch. OS18-7. P. 147–150.
Keywords: mobile robots
In book
ALife Robotics Corporation Ltd., 2020.
Mirzoian V., Mustafin M., Magid E., , in: Proceedings Of The 2024 International Conference On Artificial Life And Robotics February 22 To 25, 2024 J:Com Horutohall, Oita, Japan. 29Th Arob International Meeting Series.: ALife Robotics Corporation Ltd., 2024. P. 281–285.
Added: February 19, 2025
Implementation of Bug1 and Bug2 Basic Path-Planning Algorithms for a TurtleBot 3 Robot in ROS Noetic
Spektor I., Zagirov A., Safin R. et al., , in: Proceedings Of The 2024 International Conference On Artificial Life And Robotics February 22 To 25, 2024 J:Com Horutohall, Oita, Japan. 29Th Arob International Meeting Series.: ALife Robotics Corporation Ltd., 2024. P. 272–275.
Added: February 19, 2025
Kirill Muravyev, Yakovlev K., IEEE Access 2023 Vol. 11 P. 132683–132698
Mapping is one of the key components of mobile robot navigation. Representing a map as a topological structure is suitable for fast path planning and does not require high positioning precision or high computational resources, which is particularly useful in large environments. In recent years, numerous methods of topological graph building have emerged. Most of ...
Added: March 19, 2024
Dergachev S., Yakovlev K., Муравьев К. Ф., , in: IFAC-PapersOnLineVol. 55. Issue 38: 13th IFAC Symposium on Robot Control SYROCO 2022.: Elsevier, 2022. P. 80–85.
Safe navigation in uneven terrains is an important problem in robotic research. In this paper we propose a 2.5D navigation system which consists of elevation map building, path planning and local path following with obstacle avoidance. For local path following we use Model Predictive Path Integral (MPPI) control method. We propose novel cost-functions for MPPI ...
Added: September 8, 2023
Sagitov A., Takano T., Muto S. et al., , in: 2019 International Conference on Artificial Life and Robotics (ICAROB).: ALife Robotics Corporation Ltd., 2019. Ch. OS4-4 P. 120–123.
Reinforcement learning based approaches show promises in various robotic applications, but a significant amount of time and resources are required for a robot to learn optimal behavior. Using virtual environments, we could significantly speed up and improve performance of a target task. We implemented a reinforcement learning based exploration algorithm for a mobile robot, training ...
Added: November 9, 2021
Safin R., Lavrenov R., Hsia K. et al., , in: 2022 International Siberian Conference on Control and Communications (SIBCON).: IEEE, 2022. Ch. 9438875.
Added: October 11, 2021
DAAAM International Publishing, 2018.
The 29th DAAAM International Symposium on Intelligent Manufacturing and Automation took place in Zadar, Croatia between the 24th and 27th October 2018, during the DAAAM International Week. The Symposium was organized by DAAAM International Vienna in cooperation with ÖIAV 1848, Vienna University of Technology, International Academy of Engineering and University of Applied Sciences – Technikum ...
Added: December 25, 2018
Мордвинов Д. А., Литвинов Ю. В., Bryksin T., , in: Proceedings of the 20th Conference of Open Innovations Association FRUCT.: FRUCT Oy, 2017. P. 296–308.
This paper presents TRIK Studio - an environment for visual (and textual) programming of robotic kits, which is used in educational organizations across Russia and Europe. First part of the article provides overview of the system - its purpose, features, differences from similar programming environments, general difficulties of robot programming and solutions proposed by TRIK ...
Added: October 31, 2018