Five AI Limited

A computer implemented method of path verification in a computer system is described. A user provides input to mark a displayed image of a scenario. A path is generated representing the trajectory of a vehicle. Control points along the path are recorded, each control point associated with a vehicle position and target speed. A vehicle position end target speed of two control points is used to calculate at least one path verification parameter which defines how a vehicle travelling along the path would behave. The at least one verification parameter is compared with a corresponding threshold value; and an alert is generated to the user at the user interface when the at least one path verification parameter exceeds the corresponding threshold value.

With respect to an adaptive cruise control method for autonomously adapting the speed of an ego vehicle ( 300 ) to maintain a target headway, headway being distance from the ego vehicle to a forward vehicle ( 302 ), the ego vehicle equipped with a perception system ( 100 ) for measuring a current headway and a current speed and acceleration of the forward vehicle relative to ego vehicle, the method may comprise: in response to detecting that the current headway is below the target headway, determining and implementing a deceleration strategy for increasing to the target headway; wherein the deceleration strategy is determined so as to selectively optimize for comfort in dependence on a predicted headway, the predicted headway computed for a future time instant based on the current speed and acceleration of the forward vehicle relative to the ego vehicle.

A computer-implemented method of creating one or more annotated perception inputs, the method comprising, in an annotation computer system: receiving a plurality of captured frames, each frame comprising a set of 3D structure points, in which at least a portion of a common structure component is captured; computing a reference position within at least one reference frame of the plurality of frames; generating a 3D model for the common structure component by selectively extracting 3D structure points of the at least one reference frame based on the reference position within that frame; determining an aligned model position for the 3D model within a target frame of the plurality of frames based on one or more manual alignment inputs received in respect of the target frame at a user interface whilst rendering the 3D model for manually aligning the 3D model with the common structure component in the target frame; and storing annotation data of the aligned model position in computer storage, in association with at least one perception input of the target frame for annotating the common structure component therein.

A computer-implemented method of generating lane detector outputs, the method comprising receiving a ground truth lane image containing one or more ground truth lane borders, each ground truth lane border comprising multiple border points; and generating a lane detector output image, by applying horizontal perturbations to the multiple border points of each ground truth lane border, the horizontal perturbations determined using a learned perturbation model, the learned perturbation model constructed to impose mutual correlation in the horizontal perturbations between vertically neighbouring border points of each ground truth lane border, and comprising parameters learned by performing a statistical analysis of lane detector errors computed between computed output images of a modelled lane detector and ground truth lane border annotations corresponding to the computed output images.

A directed search method is applied to a parameter space of a scenario for testing the performance of a robotic system in simulation. The directed search method is applied based multiple performance evaluation rules. A performance predictor is trained to probabilistically predict a pass or fail result for each rule at each point in the parameter space. An overall acquisition function is determined as follows: if a pass outcome is predicted at a given, the performance evaluation rule having the highest probability of an incorrect outcome prediction at determines the acquisition function; whereas, if a fail outcome is predicted at a given point for at least one rule, then the acquisition function is determined by the performance evaluation rule for which a fail outcome is predicted with the lowest probability of an incorrect outcome prediction.

A computer-implemented method of determining control actions for controlling a mobile robot comprises: receiving a set of scenario description parameters describing a scenario and a desired goal for the mobile robot therein; in a first constrained optimization stage, applying a first optimizer to determine a first series of control actions that substantially globally optimizes a preliminary cost function for the scenario, the preliminary cost function based on a first computed trajectory of the mobile robot, as computed by applying a preliminary robot dynamics model to the first series of control actions, and in a second constrained optimization stage, applying a second optimizer to determine a second series of control actions that substantially globally optimizes a full cost function for the scenario, the full cost function based on a second computed trajectory of the mobile robot, as computed by applying a full robot dynamics model to the second series of control actions; wherein initialization data of at least one of the first computed trajectory and the first series of control actions is used to initialize the second optimizer for determining the second series of control actions, and wherein the preliminary robot dynamic model approximates the full robot dynamics model, the cost functions embody similar objectives to each encourage achievement of the desired goal, and both are optimized with respect to similar hard constraints, such that the initialization data guides the second optimizer to the substantially globally-optimal second series of control actions.

A directed search method is applied to a parameter space of a scenario for testing the performance of a robotic system in simulation. The directed search method is applied based on at least one performance evaluation rule that returns a performance score that can be numerical or non-numerical. A hierarchical score prediction model is constructed as follows. A score classification model is trained to probabilistically predict whether a point in the parameter space will result in a numerical or non-numerical outcome. A score regression model is trained to probabilistically predict a performance score for a given point, given that the score is numerical. The score classification and regression models are used to guide a directed search of the parameter space towards the most salient instances of the scenario.

A computer-implemented method of perceiving structure in an environment comprises steps of: receiving at least one structure observation input pertaining to the environment; processing the at least one structure observation input in a perception pipeline to compute a perception output; determining one or more uncertainty source inputs pertaining to the structure observation input; and determining for the perception output an associated uncertainty estimate by applying, to the one or more uncertainty source inputs, an uncertainty estimation function learned from statistical analysis of historical perception outputs.

A computer-implemented method of creating 2D annotation data for annotating one or more perception inputs comprises: receiving at the annotation computer system at least one captured frame comprising a set of 3D structure points, in which at least a portion of a structure component is captured; computing a reference position for the structure component within the frame; generating a 3D model for the structure component by selectively extracting 3D structure points of the frame based on the reference position; computing a projection of the 3D model into an image plane; and storing 2D annotation data of the computed projection in persistent computer storage for annotating the structure component within the image plane.

A method of generating at least one trajectory in scenario comprising an agent navigating a mapped area, the method comprising: receiving an observed state of the agent and map data of the mapped area; generating a set of multiple trajectory basis elements from the observed state of the agent based on the map data; processing one or more scenario inputs in a neural network to generate a set of weights, each weight corresponding to one of the trajectory basis elements; and generating a trajectory for the agent by weighting each trajectory basis element by its corresponding weights and combining the weighted trajectory basis elements.