Introduction to Autonomous Mobile Robots

By Roland Yves Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza. 2004

2,868 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/b7728ad7ee4332f19e7c83c1858551f97b0884e5

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In Computer Vision and Pattern Recognition

In Control and Systems Engineering

Citations in the corpus

Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach (2012, background): “In robotics, the generation of trajectories with avoidance constraints has been extensively studied.”
Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review (2020, neutral): “Passive sensors produce outputs by sensing the surrounding energy using cameras and GPS, while active sensors transmit energy and measure the reﬂected energy to produce outputs (LiDAR and Radar) [12].”
The e-puck, a Robot Designed for Education in Engineering (2009, background): “They are usually implemented using expensive sensors such as laser range finder [19], which, because of limited education budgets, often restricts their teaching to simulation.”
Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda (2021, background): “A high level of manoeurability can be achieved by powering Swedish or spherical wheels r increasing the number of legs, thus allowing the robot to move t any time in any direction along the ground plane regardless of he orientation of the robot ( Siegwart et al. , 2011 ).”
Real-time monocular visual odometry for on-road vehicles with 1-point RANSAC (2009, methodology): “For a wheeled vehicle to exhibit rolling motion, a point must exist around which each wheel of the vehicle follows a circular course [17].”
A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods (2020, background): “Furthermore, an active sensor may suffer from interference between its signal and environment [11].”
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers (2022, background): “To operate autonomously, a robot needs to form a model of the surrounding environment—including localization and mapping—and perform safe navigation [1].”