Modeling dynamic scenarios for local sensor-based motion planning

Montesano, Luis; Mínguez, Javier; Montano, Luis

doi:10.1007/s10514-008-9092-9

Cited by 37 publications

(21 citation statements)

References 44 publications

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“…Another approach involves tracking these "moving" landmarks and labelling them as dynamic [8]. In general, these approaches can handle some problems of navigating in a dynamic environment, but they cannot deal with long-term changes to the structure of the environment.…”

Section: Related Workmentioning

confidence: 99%

Persistent localization and life-long mapping in changing environments using the Frequency Map Enhancement

Krajník

Fentanes

Hanheide

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-We present a lifelong mapping and localisation system for long-term autonomous operation of mobile robots in changing environments. The core of the system is a spatiotemporal occupancy grid that explicitly represents the persistence and periodicity of the individual cells and can predict the probability of their occupancy in the future. During navigation, our robot builds temporally local maps and integrates then into the global spatio-temporal grid. Through re-observation of the same locations, the spatio-temporal grid learns the longterm environment dynamics and gains the ability to predict the future environment states. This predictive ability allows to generate time-specific 2d maps used by the robot's localisation and planning modules. By analysing data from a long-term deployment of the robot in a human-populated environment, we show that the proposed representation improves localisation accuracy and the efficiency of path planning. We also show how to integrate the method into the ROS navigation stack for use by other roboticists.

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Section: Related Workmentioning

confidence: 99%

Persistent localization and life-long mapping in changing environments using the Frequency Map Enhancement

Krajník

Fentanes

Hanheide

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…A binary occupancy grid map was chosen to model the static obstacles as well as the free space, and a set of extended Kalman filters was chosen to track the moving objects around the robot. A specific technique [31] was used to correct the robot's position, update the map, and detect and track the moving objects around the robot. The static map traveled centered on the robot.…”

Section: B Autonomous Navigation Systemmentioning

confidence: 99%

A Noninvasive Brain-Actuated Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation

et al. 2009

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Abstract-This paper describes a new noninvasive brainactuated wheelchair that relies on a P300 neurophysiological protocol and automated navigation. When in operation, the user faces a screen displaying a real-time virtual reconstruction of the scenario and concentrates on the location of the space to reach. A visual stimulation process elicits the neurological phenomenon, and the electroencephalogram (EEG) signal processing detects the target location. This location is transferred to the autonomous navigation system that drives the wheelchair to the desired location while avoiding collisions with obstacles in the environment detected by the laser scanner. This concept gives the user the flexibility to use the device in unknown and evolving scenarios. The prototype was validated with five healthy participants in three consecutive steps: screening (an analysis of three different groups of visual interface designs), virtual-environment driving, and driving sessions with the wheelchair. On the basis of the results, this paper reports the following evaluation studies: 1) a technical evaluation of the device and all functionalities; 2) a users' behavior study; and 3) a variability study. The overall result was that all the participants were able to successfully operate the device with relative ease, thus showing a great adaptation as well as a high robustness and low variability of the system.

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“…There have been different approaches to include these changes in the model of the environment for example by removing moving objects from the representation of the environment [5], [6] or by tracking these objects and classifying them as moving landmarks [7], [8], [9]. In [10] a new map type that represents local maps at different time scales is presented, where the best map for localisation is chosen by its consistency with current readings.…”

Section: Related Workmentioning

confidence: 99%

Long-term topological localisation for service robots in dynamic environments using spectral maps

Krajník

Fentanes

Mozos

et al. 2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-This paper presents a new approach for topological localisation of service robots in dynamic indoor environments. In contrast to typical localisation approaches that rely mainly on static parts of the environment, our approach makes explicit use of information about changes by learning and modelling the spatio-temporal dynamics of the environment where the robot is acting. The proposed spatio-temporal world model is able to predict environmental changes in time, allowing the robot to improve its localisation capabilities during longterm operations in populated environments. To investigate the proposed approach, we have enabled a mobile robot to autonomously patrol a populated environment over a period of one week while building the proposed model representation. We demonstrate that the experience learned during one week is applicable for topological localization even after a hiatus of three months by showing that the localization error rate is significantly lower compared to static environment representations.

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Modeling dynamic scenarios for local sensor-based motion planning

Cited by 37 publications

References 44 publications

Persistent localization and life-long mapping in changing environments using the Frequency Map Enhancement

Persistent localization and life-long mapping in changing environments using the Frequency Map Enhancement

A Noninvasive Brain-Actuated Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation

Long-term topological localisation for service robots in dynamic environments using spectral maps

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