Q-bot Limited

Huawei Technologies Co., Limited

Miguel Cristobal

Matthew Holloway

Panji Setiawan

Daniel Taylor

Peter Childs

Thomas Lipinski

A device and method perform Simultaneous Localization and Mapping (SLAM). The device includes at least one processor configured to perform the SLAM method, which includes the following operations. Preprocess, in a first processing stage, a received data sequence including multiple images recorded by a camera and sensor readings from multiple sensors in order to obtain a frame sequence. Each frame of the frame sequence includes a visual feature set related to one of the images at a determined time instance and sensor readings from that time instance. Sequentially process, in a second processing stage, each frame of the frame sequence based on the visual feature set and the sensor readings included in that frame in order to generate a sequence mapping graph. Merge, in a third processing stage, the sequence mapping graph with at least one other graph, in order to generate or update a full graph.

Device and method for performing simultaneous localization and mapping

The present disclosure provides a method of processing depth data and image data from a robotic device having a camera and a depth measurement device mounted to a chassis of the robotic device to generate a data set representative of a three-dimensional map of an environment in which the robotic device is located. The camera is arranged to generate image data relating to the environment. The depth measurement device is arranged to generate depth data relating to the environment. The method comprises generating image data and depth data at a first location of the robotic device in the environment, whereby to generate a first data set comprising a plurality of data points. The method further comprises moving the robotic device to at least a second location in the environment. The method further comprises generating image data and depth data at the second location, whereby to generate a second data set comprising a plurality of data points. The method further comprises associating each data point of the first data set with the spatially nearest point of the second data set, if any, within a predefined distance from the first data point. The method further comprises replacing data points from the first data set with the associated data points from the second data set by reference to the distance of the data point from the location of the robotic device when the data point was generated.

Autonomous surveying of underfloor voids

A robotic vehicle, in particular for spraying insulation material, comprises a chassis (), at least two driven wheels () having a common axis of rotation, and a wheel connecting member () which connects the two wheels (). The wheel connecting member () is connected to the chassis by a pivotal connection which allows the wheel connecting member to pivot with respect to the chassis about a pivoting axis transverse to the common axis of rotation of the wheels. The wheel connecting member () may be removably mounted to the chassis ().

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Munich, Germany

Miguel Cristobal