Methods, devices and instruction-carrying storage operate to track a target object over time and space. The tracking techniques involve obtaining a point cloud of reflection points at time n, a target from time n−1, state information including previous location information for the target and previous group distribution for previous reflection points associated with the target at time n−1; predicting a location of the target at time n based on the state information; determining a gate around the target and which of the multiple reflection points are within the gate; determining, for each of the multiple reflection points determined to be within the gate, a likelihood that the corresponding reflection point is associated with the target; determining current group distribution for the reflection points determined to likely be associated with the target; and outputting the determined current group distribution and current location information of the target.

Systems and methods for route synchronization between two or more robots to allow for a single training run of a route to effectively train multiple robots to follow the route.

A method for fusing a first occupancy map and a second occupancy map comprises: determining at least one fusion parameter representing a potential dissimilarity between the first occupancy map and the second occupancy map and determining a fused occupancy map representing free and occupied space around the vehicle. The fused occupancy map is determined based on the first occupancy map, the second occupancy map, and a fusion rule. The fusion rule is configured to control the influence of the first occupancy map and/or the second occupancy map on the fused occupancy map based on the at least one fusion parameter.

Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.

A vehicle sensor device (1) includes an outer cover (12), a sensor unit (20) that transmits and receives an electromagnetic wave through the outer cover (12) and outputs a signal related to the electromagnetic wave incident on an inner side of the outer cover (12), a heater (30) that is provided in the outer cover (12) and heats a transmission region (AR) of the outer cover (12) through which the electromagnetic wave emitted from the sensor unit (20) passes, and a control unit (CO). The control unit (CO) outputs a detection signal of an object located outside the outer cover (12) based on the signal from the sensor unit (20) in at least a part of a period in which the heater (30) is OFF, and stops outputting of the detection signal in at least a part of a period in which the heater (30) is ON.

In various examples, surface profile estimation and bump detection may be performed based on a three-dimensional (3D) point cloud. The 3D point cloud may be filtered in view of a portion of an environment including drivable free-space, and within a threshold height to factor out other objects or obstacles other than a driving surface and protuberances thereon. The 3D point cloud may be analyzed—e.g., using a sliding window of bounding shapes along a longitudinal or other heading direction—to determine one-dimensional (1D) signal profiles corresponding to heights along the driving surface. The profile itself may be used by a vehicle—e.g., an autonomous or semi-autonomous vehicle—to help in navigating the environment, and/or the profile may be used to detect bumps, humps, and/or other protuberances along the driving surface, in addition to a location, orientation, and geometry thereof.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

An example method includes gathering, via a first module of a first type, first simultaneous localization and mapping data and gathering, via a second module of a second type, second simultaneous localization and mapping data. The method includes generating, via a simultaneous localization and mapping module, a first map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the first map being of a first map type and generating, via the simultaneous localization and mapping module, a second map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the second map being of a second map type. The map of the first type is used by vehicles with module(s) of the first and/or second types and the map of the second type is used by vehicles with a module of the second type exclusively.

A sensor assembly can include a housing that includes a view pane and a mounting feature configured to replace a trailer light of a cargo trailer of a semi-trailer truck. The sensor assembly can also include a lighting element mounted within the housing to selectively generate light, and a sensor mounted within the housing and having a field of view through the view pane. The sensor assembly can also include a communication interface configured to transmit sensor data from the sensor to a control system of the self-driving tractor.

A system that includes a vehicle horn can reduce noise pollution caused by vehicles. The system can include a vehicle horn that has a signal-based mode and a sound-based mode. In the signal-based mode, the vehicle horn can output an electronic signal. In the sound-based mode, the vehicle horn can output an audible signal. The system can select one of the signal-based mode and the sound-based mode for the vehicle horn based on the driving environment data acquired by one or more sensors. Upon receiving a horn command, the system can cause the vehicle horn to output a signal based on the selected mode.