Abstract:
A method for modelling a dataset includes a training phase, wherein the dataset is applied to a non-stationary Gaussian process kernel in order to optimize the values of a set of hyperparameters associated with the Gaussian process kernel, and an evaluation phase in which the dataset and Gaussian process kernel with optimized hyperparameters are used to generate model data. The evaluation phase includes a nearest neighbor selection step. The method may include generating a model at a selected resolution.
Abstract:
A planning system (201) for scheduling the operation of autonomous entities within a defined geographical region. The planning system operates at a region plan level (301) for strategic planning across the geographical region, at an operation plan level (302) for operations to be performed by autonomous entities in localized zones having operation-defined geographical boundaries, and at a task plan level (303) in which processing is undertaken in respect of specific tasks to be performed by the autonomous entities, in undertaking the operations.
Abstract:
Methods and systems are described for tracking material through a production chain or operational process chain in which the material is transferred via a plurality of spatially distinct lumped masses of material (12, 14, 16, 18). A dynamic state space (430) is maintained descriptive of the plurality of spatially distinct lumped masses of material, wherein a quantity of entries in the dynamic state space is augmented or diminished dependent on a quantity of spatially distinct lumped masses being tracked. Measurements relating to an observed lumped mass of material are fused into the dynamic state space and a dynamic covariance matrix to provide an updated estimate of material in the plurality of spatially distinct lumped masses of material.
Abstract:
A hierarchical control system (203) for supervising operations of an autonomous operator located within a defined geographical region containing a localized zone having an operation-defined boundary. The control system (203) has a primary controller (604) associated with the defined geographical region and a secondary controller (605) associated with the localized zone. The secondary controller (605) is responsive to the supervisory control of the primary controller (604). The autonomous operator, if located within the localized zone, is responsive to the supervisory control of the secondary controller (605).
Abstract:
Apparatus and method for obtaining information from drilled holes for mining A mobile vehicle (11) is operated autonomously to approach a hole (13a) from which information is to be obtained. An onboard perception system (17) detects the exact location of the hole and an onboard sensor (26) is deployed from the vehicle into the hole. Perception system (17) comprises a number of scanners (23) carried by a mounting (24) fitted to the rear of the vehicle. A downhole sensor unit (18) movable along a swinging arm (19) carries downhole sensors selectively lowerable into the hole by operation of cable reels within the unit (18).
Abstract:
Methods and systems are described for effecting autonomous operations within a defined geographical region (1110). A plurality of localised zones (1102, 1104, 1106, 1108) having operation-defined geographical boundaries are specified within the region. A plurality of control modules are established associated with respective ones of the localised zones and autonomous operations are effected under the supervisory control of the control module associated with the localised zone in which the autonomous operation occurs. The geographical disposition of the boundary of at least one of the localised zones is varied within the defined geographical region.
Abstract:
A method of computerized data analysis and synthesis is described. First and second datasets of a quantity of interest are stored. A Gaussian process model is generated using the first and second datasets to compute optimized kernel and noise hyperparameters. The Gaussian process model is applied using the stored first and second datasets and hyperparameters to perform Gaussian process regression to compute estimates of unknown values of the quantity of interest. The resulting computed estimates of the quantity of interest result from a non-parametric Gaussian process fusion of the first and second measurement datasets. The first and second datasets may be derived from the same or different measurement sensors. Different sensors may have different noise and/or other characteristics.
Abstract:
Described herein is a computerised method for identifying and classifying edges in a dataset representative of an open-pit mine terrain. The method includes the step of identifying one or more surfaces of the terrain having common topological attributes (306). Then, for each surface identified, edges of the identified surface are detected (308) and each of the detected edges are classified (316) as one of a toe, crest, or other than a crest or a toe. The method also includes the step of updating the dataset (208) with the edges classified as toes or crests.
Abstract:
Autonomous operations are conducted within a defined geographical region. In an autonomous system of a management party a plurality of localised zones are established having operation-defined geographical boundaries within the geographical region. Entities having autonomous operating systems to perform specific autonomous operations within respective ones of the localised zones. The autonomous system of the management party is integrated with the autonomous operating systems of the entities.
Abstract:
A planning system (201) for scheduling the operation of autonomous entities within a defined geographical region. The planning system operates at a region plan level (301) for strategic planning across the geographical region, at an operation plan level (302) for operations to be performed by autonomous entities in localised zones having operation-defined geographical boundaries, and at a task plan level (303) in which processing is undertaken in respect of specific tasks to be performed by the autonomous entities, in undertaking the operations.