Abstract: A mobile robot including a vision system, the vision system including a camera and an illumination system; the illumination system including a plurality of light sources arranged to provide a level of illumination to an area surrounding the mobile robot; and a control system for controlling the illumination system. The control system adjusts the level of illumination provided by the plurality of light sources based on an image captured by the camera; an exposure time of the camera at the time the image was captured; and robot rotation information.

Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.

Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.

Abstract: A mobile robot including a vision system, the vision system including a camera and an illumination system; the illumination system including a plurality of light sources arranged to provide a level of illumination to an area surrounding the mobile robot; and a control system for controlling the illumination system. The control system adjusts the level of illumination provided by the plurality of light sources based on an image captured by the camera; an exposure time of the camera at the time the image was captured; and robot rotation information.

Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.

Abstract: A mobile robot comprising: a vision system, the vision system comprising a camera and two or more light sources each arranged to provide a level of illumination to an area surrounding the mobile robot; wherein the two or more light sources are arranged to illuminate separate areas surrounding the robot corresponding to different sections of an image captured by the camera, and the level of illumination provided by each of the light sources is independently adjustable.

Abstract: A mobile robot comprising: a vision system, the vision system comprising a camera and at least one light source arranged to provide a level of illumination to an area surrounding the mobile robot; and a control system, the control system comprising a feature detection unit for detecting features within images captured by the vision system; wherein the level of illumination provided by the light source is adjusted in response to the number of features detected by the feature detection unit.

Abstract: A mobile robot including: a vision system, the vision system comprising a camera and at least one light source arranged to provide a level of illumination to an area surrounding the mobile robot; wherein the at least one light source is arranged on the mobile robot to emit a cone of light that illuminates an area to a side of the robot that is orthogonal to a forward direction of travel of the robot.

Abstract: A mobile robot comprising: a vision system, the vision system comprising a camera and two or more light sources each arranged to provide a level of illumination to an area surrounding the mobile robot; wherein the two or more light sources are arranged to illuminate separate areas surrounding the robot corresponding to different sections of an image captured by the camera, and the level of illumination provided by each of the light sources is independently adjustable.

Abstract: A mobile robot comprising: a vision system, the vision system comprising a camera and at least one light source arranged to provide a level of illumination to an area surrounding the mobile robot; and a control system, the control system comprising a feature detection unit for detecting features within images captured by the vision system; wherein the level of illumination provided by the light source is adjusted in response to the number of features detected by the feature detection unit.

Abstract: A method and apparatus for establishing a route for an autonomous vehicle, the method including: determining localization information for the vehicle with respect to a first frame of reference that is fixed with respect to a current state of the vehicle; determining localization information for the vehicle with respect to a second frame of reference that is fixed with respect to an entity (e.g. Earth), the vehicle being moveable with respect to the entity; establishing a route for the vehicle with respect to the second frame using the localization information for the vehicle with respect to the second frame; transforming the route from the second frame to the first frame; and determining a route for the vehicle with respect to the first frame using the localization information for the vehicle with respect to the first frame and the transformed route.

Abstract: A method and apparatus for establishing a route for an autonomous vehicle, the method including: determining localisation information for the vehicle with respect to a first frame of reference that is fixed with respect to a current state of the vehicle; determining localisation information for the vehicle with respect to a second frame of reference that is fixed with respect to an entity (e.g. Earth), the vehicle being moveable with respect to the entity; establishing a route for the vehicle with respect to the second frame using the localisation information for the vehicle with respect to the second frame; transforming the route from the second frame to the first frame; and determining a route for the vehicle with respect to the first frame using the localisation information for the vehicle with respect to the first frame and the transformed route.

Abstract: A system and method for scheduling jobs in a multiprocessor machine is disclosed. The status of CPUs on node boards in the multiprocessor machine is periodically determined. The status can indicate the number of CPUs available, and the maximum radius of free CPUs available to execute jobs. Memory allocation is also monitored. This information is provided to a scheduler that compares the status of the resources available against the resource requirements of jobs. The node boards and CPUS, as well as other resources such as memory, are arranged in hosts. The scheduler then schedules jobs to hosts that indicate they have resources available to execute the jobs. If none of the hosts indicate they have resources available to execute the jobs, the scheduler will wait until the resources become available. A best fit of job to resources is attained by scheduling jobs to hosts that have the maximum number of free CPUs for a radius corresponding to the CPU radius requirement of a job.