2016 Ieee International Conference On Simulation Modeling And Programming For Autonomous Robots Simpar
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2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)
Topics of interest include, but are not limited to 3D robot simulation and mathematical modeling of robots Machine learning Reliability, scalability and validation of robot simulation Simulated sensors and actuators Offline simulation of robot design Online simulation with real time constraints Simulation with software hardware in the loop Middleware for robotics Modeling framework for robots and environments Testing and validation of robot software Standardization for robotic services Communication infrastructures in distributed robotics Interaction between sensor networks and robots Human robot interaction and collaboration Multi robot systems
2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)
Annotation Topics of interest include, but are not limited to 3D robot simulation and mathematical modeling of robots Machine learning Reliability, scalability and validation of robot simulation Simulated sensors and actuators Offline simulation of robot design Online simulation with real time constraints Simulation with software hardware in the loop Middleware for robotics Modeling framework for robots and environments Testing and validation of robot software Standardization for robotic services Communication infrastructures in distributed robotics Interaction between sensor networks and robots Human robot interaction and collaboration Multi robot systems.
Intelligent Autonomous Systems 15
This book presents the latest advances and research achievements in the fields of autonomous robots and intelligent systems, presented at the IAS-15 conference, held in Baden-Baden, Germany, in June 2018. It brings together contributions from researchers, engineers and practitioners from all over the world on the main trends of robotics: navigation, path planning, robot vision, human detection, and robot design – as well as a wide range of applications. This installment of the conference reflects the rise of machine learning and deep learning in the robotics field, as employed in a variety of applications and systems. All contributions were selected using a rigorous peer-review process to ensure their scientific quality. The series of biennial IAS conferences was started in 1986: since then, it has become an essential venue for the robotics community.