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Robust Perception from Optical Senso...
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Schaub, Alexander.
Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles/ by Alexander Schaub.
作者:
Schaub, Alexander.
面頁冊數:
XV, 267 p. 127 illus., 123 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Control engineering. -
電子資源:
https://doi.org/10.1007/978-3-658-19087-3
ISBN:
9783658190873
Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles
Schaub, Alexander.
Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles
[electronic resource] /by Alexander Schaub. - 1st ed. 2018. - XV, 267 p. 127 illus., 123 illus. in color.online resource.
Why Mobile Robots Should Have an Artificial Instinct -- Vision-Based Reactive Controllers -- Evaluation in Real World Tests and in Simulation.
Alexander Schaub examines how a reactive instinctive behavior, similar to instinctive reactions as incorporated by living beings, can be achieved for intelligent mobile robots to extend the classic reasoning approaches. He identifies possible applications for reactive approaches, as they enable a fast response time, increase robustness and have a high abstraction ability, even though reactive methods are not universally applicable. The chosen applications are obstacle avoidance and relative positioning – which can also be utilized for navigation – and a combination of both. The implementation of reactive instinctive behaviors for the identified tasks is then validated in simulation together with real world experiments. Contents Why Mobile Robots Should Have an Artificial Instinct Vision-Based Reactive Controllers Evaluation in Real World Tests and in Simulation Target Groups Lecturers and students in the field of Robotics, Control Engineering, Computer Vision Practitioners in the field of Intelligent Vehicles, Mobile Robots About the Author Alexander Schaub joined the Robotics and Mechatronics Center of the German Aerospace Center (DLR) in 2009 and worked in the development of a robotic electric vehicle and researched in the field of vision-based control and reactive instinctive behaviors for autonomous vehicle. In 2017, he started an MBA at HEC Paris and will continue working in the field of autonomous driving afterwards.
ISBN: 9783658190873
Standard No.: 10.1007/978-3-658-19087-3doiSubjects--Topical Terms:
1249728
Control engineering.
LC Class. No.: TJ210.2-211.495
Dewey Class. No.: 629.8
Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles
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Alexander Schaub examines how a reactive instinctive behavior, similar to instinctive reactions as incorporated by living beings, can be achieved for intelligent mobile robots to extend the classic reasoning approaches. He identifies possible applications for reactive approaches, as they enable a fast response time, increase robustness and have a high abstraction ability, even though reactive methods are not universally applicable. The chosen applications are obstacle avoidance and relative positioning – which can also be utilized for navigation – and a combination of both. The implementation of reactive instinctive behaviors for the identified tasks is then validated in simulation together with real world experiments. Contents Why Mobile Robots Should Have an Artificial Instinct Vision-Based Reactive Controllers Evaluation in Real World Tests and in Simulation Target Groups Lecturers and students in the field of Robotics, Control Engineering, Computer Vision Practitioners in the field of Intelligent Vehicles, Mobile Robots About the Author Alexander Schaub joined the Robotics and Mechatronics Center of the German Aerospace Center (DLR) in 2009 and worked in the development of a robotic electric vehicle and researched in the field of vision-based control and reactive instinctive behaviors for autonomous vehicle. In 2017, he started an MBA at HEC Paris and will continue working in the field of autonomous driving afterwards.
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