Abstract: An autonomous vehicle (AV) planning method comprises: receiving sensor inputs pertaining to an AV; processing the AV sensor inputs to determine an encountered driving scenario; in an AV planner, executing a tree search algorithm to determine a sequence of AV manoeuvres corresponding to a path through a constructed game tree; and generating AV control signals for executing the determined sequence of AV manoeuvres; wherein the game tree has a plurality of nodes representing anticipated states of the encountered driving scenario, and the anticipated driving scenario state of each child node is determined by updating the driving scenario state of its parent node based on (i) a candidate AV manoeuvre and (ii) an anticipated behaviour of at least one external agent in the encountered driving scenario.

Abstract: The invention provides a computer-implemented method of planning a path for a mobile robot such as an autonomous vehicle in the presence of K obstacles. The method uses, for each of the K obstacles, a shape Bk and a density function pk(x) representing the probabilistic position of the obstacle. The method repeats the following steps for at least two different paths A: —choosing a path A, where A is the swept area of the robot within a given time interval; and—calculating based on the density function of each obstacle and the swept path an upper bound on the total probability of at least one collision FD between the robot and the K obstacles. This allows a number of candidate paths to be ranked for safety. By precomputing factors of the computational steps over K obstacles, the computation per path is O(N), and not O(NK). A safety threshold can be used to filter out paths below that threshold.

Abstract: Abstract: A driving scenario is extracted from real-world driving data captured within a road layout. A simulation is run based on the extracted driving scenario, in which an ego agent and a simulated non-ego agent each exhibit closed-loop behaviour. The closed-loop behaviour of the ego agent is determined by autonomous decisions taken in an AV stack under testing in response to simulated inputs, reactive to the simulated agent. The closed-loop behaviour of the non-ego agent is determined by implementing an inferred goal or behaviour, reactive to the ego agent. The goal or behaviour is inferred from an observed trace of a real-world agent extracted from the real-world driving data.

Abstract: A computer-implemented method of evaluating the performance of a target planner for an ego robot in a real or simulated scenario, the method comprising: receiving evaluation data for evaluating the performance of the target planner in the scenario, the evaluation data generated by applying the target planner at incrementing planning steps, in order to compute a series of ego plans that respond to changes in the scenario, the series of ego plans being implemented in the scenario to cause changes in an ego state the evaluation data comprising: the ego plan computed by the target planner at one of the planning steps, and a scenario state at a time instant of the scenario, wherein the evaluation data is used to evaluate the target planner by: computing a reference plan for said time instant based on the scenario state, the scenario state including the ego state at that time instant as caused by implementing one or more preceding ego plans of the series of ego plans computed by the target planner, and computing at

Abstract: A computer system for planning mobile robot trajectories, the computer system comprising: an input configured to receive a set of scenario description parameters describing a scenario and a desired goal for the mobile robot therein; a runtime optimizer configured to compute a final mobile robot trajectory that substantially optimizes a cost function for the scenario, subject to a set of hard constraints that the final mobile robot trajectory is guaranteed to satisfy; and a trained function approximator configured to compute, from the set of scenario description parameters, initialization data defining an initial mobile robot trajectory.

Abstract: 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 l

Abstract: Ego actions for a mobile robot in the presence of at least one agent are autonomously planned. In a sampling phase, a goal for an agent is sampled from a set of available goals based on a probabilistic goal distribution, as determined using an observed trajectory of the agent. An agent trajectory is sampled, from a set of possible trajectories associated with the sampled goal, based on a probabilistic trajectory distribution, each trajectory of the set of possible trajectories reaching a location of the associated goal. In a simulation phase, an ego action is selected from a set of available ego actions and based on the selected ego action, the sampled agent trajectory, and a current state of the mobile robot, (i) behaviour of the mobile robot, and (ii) simultaneous behaviour of the agent are simulated, in order to assess the viability of the selected ego action.

Abstract: A computer-implemented method of planning a path for a mobile robot in the presence of a set of obstacles comprises: computing for each obstacle a probabilistic obstacle position distribution; computing at least one path-independent function as a combination of the probabilistic obstacle position distributions; and for at least one candidate path, determining an upper bound on the total probability of obstacle collision along that path, by aggregating the path-independent function based on an area defined by the candidate path and a mobile robot shape, wherein the path-independent function is independent of the candidate path.

Abstract: A computer-implemented method of predicting an external actor trajectory comprises receiving, at a computer, sensor inputs for detecting and tracking an external actor; applying object tracking to the sensor inputs, in order track the external actor, and thereby determine an observed trace of the external actor over a time interval; determining a set of available goals for the external actor; for each of the available goals, determining an expected trajectory model; and comparing the observed trace of the external actor with the expected trajectory model for each of the available goals, to determine a likelihood of that goal.

Abstract: An autonomous vehicle (AV) planning method comprises: receiving sensor inputs pertaining to an AV; processing the AV sensor inputs to determine an encountered driving scenario; in an AV planner, executing a tree search algorithm to determine a sequence of AV manoeuvres corresponding to a path through a constructed game tree; and generating AV control signals for executing the determined sequence of AV manoeuvres; wherein the game tree has a plurality of nodes representing anticipated states of the encountered driving scenario, and the anticipated driving scenario state of each child node is determined by updating the driving scenario state of its parent node based on (i) a candidate AV manoeuvre and (ii) an anticipated behaviour of at least one external agent in the encountered driving scenario.

Abstract: One aspect herein provides a method of analysing driving behaviour in a data processing computer system, the method comprising: receiving at the data processing computer system driving behaviour data to be analysed, wherein the driving behaviour data records vehicle movements within a monitored driving area; analysing the driving behaviour data to determine a normal driving behaviour model for the monitored driving area; using object tracking to determine driving trajectories of vehicles driving in the monitored driving area; comparing the driving trajectories with the normal driving behaviour model to identify at least one abnormal driving trajectory; and extracting a portion of the driving behaviour data corresponding to a time interval associated with the abnormal driving trajectory.

Abstract: An electronic doorbell system can be configured to enable remote audio communications between a visitor at the doorbell and a user of a mobile computing device by exchanging speech-to-text and/or text-to-speech messages in real time. Audio captured by the visitor can be transcribed into text messages and sent to the user of the mobile device using a speech-to-text service. The user of the mobile device can send text messages to the doorbell for playback to the visitor by using a text-to-speech service. The system can also use artificial intelligence to detect the language spoken by the visitor for translating between a predetermined language of the user and the language of the visitor. The system can also include a camera for capturing video of the visitor for display to the mobile device simultaneous with exchanging text messages between the visitor and the user, such as during a live Session Initiation Protocol (SIP) communication.

Abstract: The invention provides a computer-implemented method of planning a path for a mobile robot such as an autonomous vehicle in the presence of K obstacles. The method uses, for each of the K obstacles, a shape Bk and a density function pk(x) representing the probabilistic position of the obstacle. The method repeats the following steps for at least two different paths A:—choosing a path A, where A is the swept area of the robot within a given time interval; and—calculating based on the density function of each obstacle and the swept path an upper bound on the total probability of at least one collision FD between the robot and the K obstacles. This allows a number of candidate paths to be ranked for safety. By precomputing factors of the computational steps over K obstacles, the computation per path is O(N), and not O(NK). A safety threshold can be used to filter out paths below that threshold.

Abstract: An electronic doorbell system can be configured to enable remote audio communications between a visitor at the doorbell and a user of a mobile computing device by exchanging speech-to-text and/or text-to-speech messages in real time. Audio captured by the visitor can be transcribed into text messages and sent to the user of the mobile device using a speech-to-text service. The user of the mobile device can send text messages to the doorbell for playback to the visitor by using a text-to-speech service. The system can also use artificial intelligence to detect the language spoken by the visitor for translating between a predetermined language of the user and the language of the visitor. The system can also include a camera for capturing video of the visitor for display to the mobile device simultaneous with exchanging text messages between the visitor and the user, such as during a live Session Initiation Protocol (SIP) communication.

Abstract: A unified catalog of products and services is described. In one implementation, a method may include receiving an indication of products, offered by a business, that are to be provided to a customer of the business, where the products are defined in a catalog based on a hierarchical product model. The method further includes determining pricing information relating to the products, the determination of the pricing information including: identifying, based on the catalog, a plurality of pricing formulas associated with the plurality of products, and applying the pricing formulas to determine the pricing information.

Abstract: System and method for approximating a system. A multi-parameter representation of a family of systems is stored. An embedding of the family into an abstract geometrical continuous space with a metric and defined by the parameters is determined. Coordinates of the space specify values for the parameters of systems of the family. The space includes a grid of points representing respective discrete approximations of the systems. A first point corresponding to a desired instance of a system is determined. The first point's coordinates specify values for the parameters of the instance. The space is sampled using a mapping of a well-distributed point set from a Euclidean space of the parameters to the abstract space. A nearest discrete point to the first point is determined which specifies values for parameters for an optimal discrete approximation of the desired instance, which are useable to implement the discrete approximation of the desired instance.

Abstract: System and method for programmatically generating a second graphical program associated with a second programming development environment based on a first graphical program associated with a first programming development environment. The second graphical program may be generated programmatically, without relying on user input, or may prompt for user input to determine various options to use in generating the second graphical program. The second graphical program may implement the functionality of, or a portion of the functionality of, the first graphical program. The method preferably generates the second graphical program such that the second programming development environment is operable to treat the second graphical program identically to a graphical program interactively developed by a user using the second programming development environment.

Abstract: System and method for programmatically generating a second graphical program associated with a second programming development environment based on a first graphical program associated with a first programming development environment. The second graphical program may be generated programmatically, without relying on user input, or may prompt for user input to determine various options to use in generating the second graphical program. The second graphical program may implement the functionality of, or a portion of the functionality of, the first graphical program. The method preferably generates the second graphical program such that the second programming development environment is operable to treat the second graphical program identically to a graphical program interactively developed by a user using the second programming development environment.

Abstract: System and method for approximating a system. A multi-parameter representation of a family of systems is stored. An embedding of the family into an abstract geometrical continuous space with a metric and defined by the parameters is determined. Coordinates of the space specify values for the parameters of systems of the family. The space includes a grid of points representing respective discrete approximations of the systems. A first point corresponding to a desired instance of a system is determined. The first point's coordinates specify values for the parameters of the instance. The space is sampled using a mapping of a well-distributed point set from a Euclidean space of the parameters to the abstract space. A nearest discrete point to the first point is determined which specifies values for parameters for an optimal discrete approximation of the desired instance, which are useable to implement the discrete approximation of the desired instance.

Abstract: System and method for programmatically generating a second graphical program associated with a second programming development environment based on a first graphical program associated with a first programming development environment. The second graphical program may be generated programmatically, without relying on user input, or may prompt for user input to determine various options to use in generating the second graphical program. The second graphical program may implement the functionality of, or a portion of the functionality of, the first graphical program. The method preferably generates the second graphical program such that the second programming development environment is operable to treat the second graphical program identically to a graphical program interactively developed by a user using the second programming development environment.