Simon Thompson

Fast sum of absolute differences visual landmark detector

This paper presents various optimisation that can be applied to the sum of absolute differences (SAD) correlation algorithm for automated landmark detection. This has applications in mobile robotic navigation and mapping. We show how some assumptions about the environment and the generic form of strong landmarks selected by the SAD correlation algorithm have led to the development of an algorithm to enable near real tune selection of strong landmarks from visual information. The landmarks that have been selected from a series of frames using our optimisation are shown to be stable through the image sequence, demonstration the scale invariance of the landmarks that are selected by the SAD correlation algorithm.

Accurate local positioning using visual landmarks from a panoramic sensor

Presents a method for representing places using a set of visual landmarks from a panoramic sensor that allows for accurate local positioning while still providing efficient global localisation. For each place landmarks are selected for their local uniqueness in the panoramic visual field and their dynamic reliability over a turn back and look movement. During this movement, the depth of landmarks is also estimated using a bearing only SLAM approach. Accurate local position tracking within places equal to that of laser range finder systems is obtained by the application of the condensation algorithm over individual places. A topological map of such places is built and both global localisation and position tracking experiments are carried out.

Path shortening and smoothing of grid-based path planning with consideration of obstacles

This paper describes a path smoothing method that results in paths with clothoidal curvature and which includes a safety margin from obstacles. The method modifies grid based A* results, and tries to push the given path away from obstacles. A technique to take into account the initial direction of robot is also shown.

Mobile robot localization using circular correlations of panoramic images

In order to determine both location and orientation of a mobile robot, we use omni-directional view images from a camera mounted on top of the robot. Images are sampled circularly on rings at various radii. Correlation values between rings of different images are regarded as the similarity of the image, therefore the similarity of locations. Using real images taken at different times in navigation experiments, we computed correlation values normalized by brightness, and confirmed the robot can be localized in 50 cm to 100 cm range with 3-10 degree orientation accuracy. The idea of using aggregated sum of circular samples for representing landmarks at multiple levels is also presented.

Home robot service by ceiling ultrasonic locator and microphone array

This paper describes a mobile robot for home service purpose together with ceiling attached ultrasonic locator and microphone array. User call can be detected by those ceiling devices and then mobile robot navigates toward given location. After reaching to the given location, the robot tries to find out user location by using stereo camera, laser and triconcentric microphone array. We implemented those system at our experimental house Rokko Holone. System components and experimental results are shown

“Calling from the other room” by Ceiling Ultrasonic Locator and Microphone Array

This paper describes a mobile robot for home service purpose together with ubiquitous ceiling ultrasonic locator and microphone array. User call can be detected by those ubiquitous devices and then mobile robot navigates toward given location. After reaching to the given location, the robot tries to find out user location by using stereo camera, laser and onbody microphone array. We implemented those system at our experimental house Rokko Holone. System components and experimental results are shown.

Accurate vision based position tracking between places in a topological map

This paper presents a method for accurately tracking the position of a mobile robot which moves between places in a previously learned topological map. Places in the map are represented by sets of visual landmarks extracted from panoramic images. Probabilistic localisation methods and the landmark representation enable position tracking within places. A sensor model is presented which improves the accuracy of local position estimates, and is robust in the presence of occlusion and data association errors. Position tracking between places requires the recognition of place transition events and the passing of local position estimates between places. This paper presents such a system and reports real world position tracking results from paths through topological maps.

Associating spoken commands with multiple human users in a dynamic environment

This paper presents a method for combining human tracking information with recognised sound commands extracted from localised and separated sound sources, enabling spoken commands to be placed in the context of an inhabited, dynamic environment. Humans are tracked using a laser range finder based system which extracts and tracks leg profiles from the raw range data. A 32 channel microphone array localises (angular) and separates different sound sources in the environment and feeds segmented sounds into a speech recognition system. Human tracking position estimates, sound source localisation results, and recognised commands are associated by probabilistic matching over time of the angle of observation from both the command sound source and the human position estimates. Experiments are conducted verifying the command recognition system and the ability to associate commands with humans in the case of a single human giving commands from multiple locations, and also multiple humans giving commands from multiple locations.

Evaluating 3D Polygon Maps for Mobile Robot Localisation

Real time localisation of mobile robots within dense 3D polygon maps is computationally expensive. Computation can be reduced by localising against an appropriate sub-set of polygons, and methods have been suggested as to how to select particular sub-sets. In the absence of detailed experimental results it can be difficult to determine if a sub-set is useful for localization. In this study we propose a method for evaluating sets of polygons for their localization utility within an environment map, or a sub region thereof, based on the rate of the change in expected sensor measurements against change in position. The measure is described, a localization map of an example environment presented, and the measure is used to compare various polygon sub-sets. Finally predicted localisation utility is evaluated against actual localisation results.