ROS

The Robot Operating System (ROS) is a flexible framework for writing robot software. It is a collection of tools, libraries, and conventions that aim to simplify the task of creating complex and robust robot behavior across a wide variety of robotic platforms. Why? Because creating truly robust, general-purpose robot software is hard. From the robot’s perspective, problems that seem trivial to humans often vary wildly between instances of tasks and environments. Dealing with these variations is so hard that no single individual, laboratory, or institution can hope to do it on their own. As a result, ROS was built from the ground up to encourage collaborative robotics software development. For example, one laboratory might have experts in mapping indoor environments, and could contribute a world-class system for producing maps. Another group might have experts at using maps to navigate, and yet another group might have discovered a computer vision approach that works well for recognizing small objects in clutter. ROS was designed specifically for groups like these to collaborate and build upon each other’s work, as is described throughout this site


References in zbMATH (referenced in 28 articles )

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  1. Tysse, Geir Ole; Cibicik, Andrej; Tingelstad, Lars; Egeland, Olav: Lyapunov-based damping controller with nonlinear MPC control of payload position for a knuckle boom crane (2022)
  2. Yang, Liwei; Fu, Lixia; Li, Ping; Mao, Jianlin; Guo, Ning; Du, Linghao: LF-ACO: an effective formation path planning for multi-mobile robot (2022)
  3. Ales Jelinek, Adam Ligocki, Ludek Zalud: Robotic Template Library (2021) arXiv
  4. Bersani, Marcello M.; Soldo, Matteo; Menghi, Claudio; Pelliccione, Patrizio; Rossi, Matteo: PuRSUE -- from specification of robotic environments to synthesis of controllers (2020)
  5. Khan, Ameer Tamoor; Li, Shuai; Chen, Dechao; Li, Yangming: Open-source projects for autonomous robotics and systems: a survey (2020)
  6. Krivic, Senka; Cashmore, Michael; Magazzeni, Daniele; Szedmak, Sandor; Piater, Justus: Using machine learning for decreasing state uncertainty in planning (2020)
  7. Listov, Petr; Jones, Colin: PolyMPC: an efficient and extensible tool for real-time nonlinear model predictive tracking and path following for fast mechatronic systems (2020)
  8. Rosu, Radu Alexandru; Quenzel, Jan; Behnke, Sven: Semi-supervised semantic mapping through label propagation with semantic texture meshes (2020)
  9. Savino, Heitor J.; Pimenta, Luciano C. A.; Shah, Julie A.; Adorno, Bruno V.: Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators (2020)
  10. Alcaina, J.; Cuenca, A.; Salt, J.; Casanova, V.; Pizá, R.: Delay-independent dual-rate PID controller for a packet-based networked control system (2019)
  11. Buiu, Cătălin; Florea, Andrei George: Membrane computing models and robot controller design, current results and challenges (2019)
  12. Casini, Daniel; Blaß, Tobias; Lütkebohle, Ingo; Brandenburg, Björn B.: Response-time analysis of ROS 2 processing chains under reservation-based scheduling (2019)
  13. Fan Fei, Zhan Tu, Yilun Yang, Jian Zhang, Xinyan Deng: Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals (2019) arXiv
  14. Ozsoyeller, Deniz; Beveridge, Andrew; Isler, Volkan: Rendezvous in planar environments with obstacles and unknown initial distance (2019)
  15. Rego, Brenner S.; Raffo, Guilherme V.: Suspended load path tracking control using a tilt-rotor UAV based on zonotopic state estimation (2019)
  16. Atsushi Sakai, Daniel Ingram, Joseph Dinius, Karan Chawla, Antonin Raffin, Alexis Paques: PythonRobotics: a Python code collection of robotics algorithms (2018) arXiv
  17. Hester, Todd; Stone, Peter: Intrinsically motivated model learning for developing curious robots (2017)
  18. Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare: Multi-robot systems implementing complex behaviors under time-varying topologies (2017)
  19. Huang, Wanrong; Wang, Yanzhen; Yang, Hai; Yi, Xiaodong; Yang, Xuejun: Distributed control for formation switch of fixed wing MAVs (2016)
  20. Wilkowski, Artur; Kornuta, Tomasz; Stefańczyk, Maciej; Kasprzak, Włodzimierz: Efficient generation of 3D surfel maps using RGB-D sensors (2016)

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