Automatic map acquisition for navigation in domestic environments

Althaus, Philipp; Christensen, Henrik I.

doi:10.1109/robot.2003.1241815

Cited by 17 publications

(14 citation statements)

References 11 publications

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“…Since we are interested in actually using the information that can be obtained from human users guiding the robot, we use data sets acquired during user studies [12, and ongoing] to understand, how users guide a robot around and present an environment, and in how far the robot's representation -in this case the structural ambiguity detection -corresponds to 1 former ActivMedia Robotics the user's understanding. Thus, we discuss our approach here in the context of a number of different data sets, obtained a) during a user study in our lab environment, b) as part of a public data set 2 acquired in domestic settings with respect to the "home tour" scenario 3 c) during an ongoing user study in domestic environments.…”

Section: Discussionmentioning

confidence: 99%

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Detecting structural ambiguities and transitions during a guided tour

Topp

Christensen

2008

2008 IEEE International Conference on Robotics and Automation

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Abstract-Service robots designed for domestic settings need to navigate in an environment that they have to share with their users. Thus, they have to be able to report their current state and whereabouts in a way that is comprehensible for the user. Pure metric maps do not usually correspond to the understanding of the environment a user would provide. Thus, the robotic map needs to be integrated with the human representation. With our framework for Human Augmented Mapping we aim to deal with this issue and assume a guided tour as basis for an initial mapping process. During such a tour the robotic system needs to be able to detect significant changes in its environment representation -structural ambiguitiesto be able to invoke a clarification discourse with the user. In this paper we present our approach to the detection of such ambiguities, that is independent from prior specification and training of particular spatial categories. We evaluate our method on data sets obtained during several runs in indoor environments in the context of a guided tour scenario.

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Section: Discussionmentioning

confidence: 99%

“…An earlier approach to supervised learning of topology was reported by Althaus and Christensen [1]. They had a user guiding a robot through an office environment and assumed an explicit external trigger given by the user, when a new node in the topological graph had to be created.…”

Section: B Mapping and Interactionmentioning

confidence: 99%

Detecting structural ambiguities and transitions during a guided tour

Topp

Christensen

2008

2008 IEEE International Conference on Robotics and Automation

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“…A limitation of our implementation is the computational complexity of O(n 2 ) for the covariance update, which limits the number of landmarks that can be handled by SLAM in real-time (this problem is not encountered in the topological mapping approach used in [1]). However, we have successfully demonstrated real-time SLAM with over 200 landmarks.…”

Section: Summary and Future Workmentioning

confidence: 99%

“…Map building is therefore a fundamental problem for which a variety of solutions have been used in previous work, including measurement by hand [4], interactive guidance with manual control [10] or people following [1], and autonomous exploration [2]. Manual map building is time-consuming and usually not considered a practical solution for robots required to operate in different environments.…”

Section: Introductionmentioning

confidence: 99%

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Interactive SLAM using Laser and Advanced Sonar

Diosi

Taylor

Kleeman

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

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Abstract-This paper presents a novel approach to mapping for mobile robots that exploits user interaction to semiautonomously create a labelled map of the environment. The robot autonomously follows the user and is provided with a verbal commentary on the current location with phrases such as "Robot, we are in the office". At the same time, a metric feature map is generated using fusion of laser and advanced sonar measurements in a Kalman filter based SLAM framework, which is later used for localization. When mapping is complete, the robot generates an occupancy grid for use in global task planning. The occupancy grid is created using a novel laser scan registration scheme that relies on storing the path of the robot along with associated local SLAM features during mapping, and later recovering the path by matching the associated local features to the final SLAM map. The occupancy grid is segmented into labelled rooms using an algorithm based on watershed segmentation and integration of the verbal commentary. Experimental results demonstrate our mobile robot creating SLAM and segmented occupancy grid maps of rooms along a 70 metre corridor, and then using these maps to navigate between rooms.

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Binding human spatial interactions with mapping for enhanced mobility in dynamic environments

Papadakis

Rives

2016

Auton Robot

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To cite this version:Panagiotis Papadakis, Patrick Rives. Binding human spatial interactions with mapping for enhanced mobility in dynamic environments. Autonomous Robots, Springer Verlag, 2017, 41 (5) Abstract For mobile robots to operate in compliance with human presence, interpreting the impact of human activities and responding constructively is a challenging goal. In this paper, we propose a generative approach for enhancing robot mapping and mobility in the presence of humans through a joint, probabilistic treatment of static and dynamic characteristics of indoor environments. Human spatial activity is explicitly exploited for the purpose of passage detection and space occupancy prediction while effectively discarding false positive human detections using prior map information. In turn, this allows the execution of plan trajectories within unexplored areas by using human presence for resolving the uncertainty or ambiguity that is due to dynamic events. A series of experiments with an indoor robot navigating in close human proximity within a multifloor building demonstrate the effectiveness of our approach in realistic conditions.

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Automatic map acquisition for navigation in domestic environments

Cited by 17 publications

References 11 publications

Detecting structural ambiguities and transitions during a guided tour

Detecting structural ambiguities and transitions during a guided tour

Interactive SLAM using Laser and Advanced Sonar

Binding human spatial interactions with mapping for enhanced mobility in dynamic environments

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