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Mobile robot navigation

About: Mobile robot navigation is a research topic. Over the lifetime, 14713 publications have been published within this topic receiving 263092 citations.


Papers
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Proceedings ArticleDOI
03 May 2010
TL;DR: This paper describes a navigation system that allowed a robot to complete 26.2 miles of autonomous navigation in a real office environment, including an efficient Voxel-based 3D mapping algorithm that explicitly models unknown space.
Abstract: This paper describes a navigation system that allowed a robot to complete 26.2 miles of autonomous navigation in a real office environment. We present the methods required to achieve this level of robustness, including an efficient Voxel-based 3D mapping algorithm that explicitly models unknown space. We also provide an open-source implementation of the algorithms used, as well as simulated environments in which our results can be verified.

536 citations

Proceedings ArticleDOI
22 Apr 1996
TL;DR: A new method for local obstacle avoidance by indoor mobile robots that formulates the problem as one of constrained optimization in velocity space, and is used as the basis of more sophisticated navigation behaviors, ranging from simple wandering to map-based navigation.
Abstract: We present a new method for local obstacle avoidance by indoor mobile robots that formulates the problem as one of constrained optimization in velocity space. Constraints that stem from physical limitations (velocities and accelerations) and the environment (the configuration of obstacles) are placed on the translational and rotational velocities of the robot. The robot chooses velocity commands that satisfy all the constraints and maximize an objective function that trades off speed, safety and goal-directedness. An efficient, real-time implementation of the method has been extensively tested, demonstrating reliable, smooth and speedy navigation in office environments. The obstacle avoidance method is used as the basis of more sophisticated navigation behaviors, ranging from simple wandering to map-based navigation.

534 citations

Journal ArticleDOI
01 Mar 1985
TL;DR: A learning technique is described in which the robot develops a global model and a network of places, which is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.
Abstract: A navigation system is described for a mobile robot equipped with a rotating ultrasonic range sensor. This navigation system is based on a dynamically maintained model of the local environment, called the composite local model. The composite local model integrates information from the rotating range sensor, the robot's touch sensor, and a pre-learned global model as the robot moves through its environment. Techniques are described for constructing a line segment description of the most recent sensor scan (the sensor model), and for integrating such descriptions to build up a model of the immediate environment (the composite local model). The estimated position of the robot is corrected by the difference in position between observed sensor signals and the corresponding symbols in the composite local model. A learning technique is described in which the robot develops a global model and a network of places. The network of places is used in global path planning, while the segments are recalled from the global model to assist in local path execution. This system is useful for navigation in a finite, pre-learned domain such as a house, office, or factory.

529 citations

Proceedings ArticleDOI
21 Jul 2017
TL;DR: A neural architecture for navigation in novel environments that learns to map from first-person views and plans a sequence of actions towards goals in the environment, and can also achieve semantically specified goals, such as go to a chair.
Abstract: We introduce a neural architecture for navigation in novel environments. Our proposed architecture learns to map from first-person views and plans a sequence of actions towards goals in the environment. The Cognitive Mapper and Planner (CMP) is based on two key ideas: a) a unified joint architecture for mapping and planning, such that the mapping is driven by the needs of the planner, and b) a spatial memory with the ability to plan given an incomplete set of observations about the world. CMP constructs a top-down belief map of the world and applies a differentiable neural net planner to produce the next action at each time step. The accumulated belief of the world enables the agent to track visited regions of the environment. Our experiments demonstrate that CMP outperforms both reactive strategies and standard memory-based architectures and performs well in novel environments. Furthermore, we show that CMP can also achieve semantically specified goals, such as go to a chair.

521 citations

Patent
James Allard1
01 May 2001
TL;DR: In this article, a point-and-click interface for remote control of a mobile robot and an intuitive user interface for remotely controlling the robot is presented. Butler et al. used a head-up display (HOG) to guide the user toward a target location.
Abstract: Methods of remote control of a mobile robot and an intuitive user interface for remotely controlling a mobile robot are provided. Using a point-and-click device (405), the user is able to choose a target location (430) within a heads-up display (400) toward which to move a mobile robot. Additional graphical overlays (410 &and 412) are provided to aid the user in navigating even in systems with asynchronous communication.

516 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202358
2022179
202194
2020125
2019146
2018129