Patent classifications
G05D1/00
Inferring State of Traffic Signal and Other Aspects of a Vehicle's Environment Based on Surrogate Data
A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.
EARLY NOTIFICATION OF NON-AUTONOMOUS AREA
The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.
Automatic Working System, Self-Moving Device, and Methods for Controlling Same
A self-moving device, including: a moving module, a task execution module, a control module. The control module is electrically connected to the moving module and the task execution module, controls the moving module to actuate the self-moving device to move, controls the task execution module to execute a working task. The self-moving device further includes a satellite navigation apparatus, electrically connected to the control module and configured to receive a satellite signal and output current location information of the self-moving device. The control module determines whether quality of location information output by the satellite navigation apparatus at a current location satisfies a preset condition, controls, if the quality does not satisfy the preset condition, the moving module to actuate the self-moving device to change a moving manner, to enable quality of location information output by the satellite navigation apparatus at a location after the movement to satisfy the preset condition.
METHODS OF TAKING A MEASUREMENT
According to the present invention there is provided a method of taking a measurement using a sensor mounted on an aerial vehicle, the aerial vehicle having one or more propellers and one or more motors which are selectively operable to drive the one or more propellers to rotate to cause the vehicle to fly, and a sensor mounted on the aerial vehicle, the method comprising the steps of, operating the one or more motors to drive the one or more propellers to cause the vehicle to fly; at a first time instant, slowing down or turning off said one or more motors; while the one or more motors are slowed down or turned off, taking a measurement using said sensor; at a second time instant, which is after the measurement has been taken using the sensor, operating the one or more motors again to drive the one or more propellers to cause the vehicle to fly. There is further provided a corresponding aerial vehicle.
LOW MOBILITY ASSISTANCE FOR AUTONOMOUS VEHICLES PASSENGERS
The present technology is effective to cause at least one processor to receive attributes of a sidewalk section within a threshold distance from a location selected by a passenger, determine a potential location for pick-up or drop-off of the passenger by the autonomous vehicle, receive an authorization from the passenger, and navigate the autonomous vehicle to the potential location for pick-up or drop-off. The attributes may include a respective curb height of the sidewalk section within the threshold distance. The potential location may be determined based upon a height of a portion of an autonomous vehicle and the respective curb height of the sidewalk section within the threshold distance. The authorization may confirm the potential location for pick-up or drop-off.
MIXED-MODE DRIVING OF A VEHICLE HAVING AUTONOMOUS DRIVING CAPABILITIES
Among other things, a vehicle having autonomous driving capabilities is operated in a mixed driving mode.
SYSTEM AND METHOD FOR REAL WORLD AUTONOMOUS VEHICLE TRAJECTORY SIMULATION
A system and method for real world autonomous vehicle trajectory simulation may include: receiving training data from a data collection system; obtaining ground truth data corresponding to the training data; performing a training phase to train a plurality of trajectory prediction models; and performing a simulation or operational phase to generate a vicinal scenario for each simulated vehicle in an iteration of a simulation. Vicinal scenarios may correspond to different locations, traffic patterns, or environmental conditions being simulated. Vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions.
DRONE-BASED INVENTORY MANAGEMENT METHODS AND SYSTEMS
Drone-based inventory management method and systems. One embodiment provides a drone-based inventory management system including one or more unmanned aerial vehicles (UAVs), and a central management system having an electronic processor, and a transceiver configured to communicate with the one or more UAVs. The electronic processor is configured to determine a discrepancy in inventory and select a UAV for verification. The electronic processor is also configured to determine whether weather permits UAV operation and operate the UAV in a pre-determined route when the weather permits UAV operation. The electronic processor is further configured to capture images using the UAV and determine new inventory based on captured images. The electronic processor is also configured to update inventory based on the new inventory.
TRAINING, TESTING, AND VERIFYING AUTONOMOUS MACHINES USING SIMULATED ENVIRONMENTS
In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.
REDUNDANT VEHICLE POWER DISTRIBUTION SYSTEM
A power distribution system is provided that ensures that a car is able to operate safely in an autonomous mode. The system includes multiple power rails, including a pair of safety critical power rails. Associated with each safety critical power rail is a safety switch, vehicle sensors (e.g., vehicle location and obstacle sensors), vehicle actuators (e.g., braking and steering actuators) and an autonomous control unit. If a fault is detected during vehicle initialization or general operation, the safety switch which detected the fault opens and that particular power rail is decoupled from the general purpose power rail as well as the remaining safety critical power rail. The remaining safety critical power rail is then able to provide power to a sufficient number of sensors, actuators and controllers to allow the car to safely and autonomously complete an emergency stop on the side of the road.