Abstract: A method and a system of calibration of a first lidar device and a second lidar device are described. A subset of pairs of positions of a vehicle as the vehicle moves along a path according to a predetermined path pattern are determined. Each pair from the subset of pairs includes a first position and a second position of the vehicle. A first field of view of the first lidar device when the vehicle is located at the first position overlaps with a second field of view of the second lidar device when the vehicle is located at the second position at a second time. Based on the subset of pairs, an extrinsic calibration transformation that transforms a position of the second lidar device into a calibrated position that allows to obtain a consistent view of the world between the first and the second lidar devices is determined.

Abstract: A method and a system of calibration of a first lidar device and a second lidar device are described. A subset of pairs of positions of a vehicle as the vehicle moves along a path according to a predetermined path pattern are determined. Each pair from the subset of pairs includes a first position and a second position of the vehicle. A first field of view of the first lidar device when the vehicle is located at the first position overlaps with a second field of view of the second lidar device when the vehicle is located at the second position at a second time. Based on the subset of pairs, an extrinsic calibration transformation that transforms a position of the second lidar device into a calibrated position that allows to obtain a consistent view of the world between the first and the second lidar devices is determined.

Abstract: A method and a system of calibration of a first lidar device and a second lidar device are described. Lidar returns recorded by the first and the second lidar devices as the vehicle moves along a path according to a predetermined path pattern in an environment are received. A subset of pairs of positions of the vehicle is determined. Each pair includes a first position and a second position. A first field of view of the first lidar device when the vehicle is located at the first position overlaps with a second field of view of the second lidar device when the vehicle is located at the second position. For each pair, an estimate of transformation is determined between a first subset of the lidar returns and a second subset of the lidar returns. An extrinsic calibration transformation is determined based on the estimates of the transformations.

Abstract: Systems and methods are directed to compensating for time delays. In one example, a system includes one or more processors and memory including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining first pose data indicative of a pose of a vehicle; obtaining first control data indicative of a first vehicle control command that has yet to affect control of the vehicle; determining, based at least partially on the first pose data and the first control data, predicted pose data indicative of an estimate of a pose of the vehicle that will result after the vehicle control command affects control of the vehicle; and generating, based at least partially on the predicted pose data, second control data indicative of a second vehicle control command to be applied subsequent to the first vehicle control command.

Abstract: Systems and methods are directed to monitoring the status of a vehicle controller or other autonomy system during operation of an autonomous vehicle. In one example, a system includes one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining a message from a vehicle controller. The operations further include, based at least partly on the message, determining whether a failure mode exists. The operations further include providing, in response to determining the failure mode exists, one or more commands to implement a safety measure response for the autonomous vehicle.

Abstract: Systems and methods for autonomous vehicle testing are provided. In one example embodiment, a computer-implemented method includes presenting, by a computing system, a visual representation of a simulated environment via a user interface on a display device. The simulated environment includes a simulated object and a simulated autonomous vehicle. The method includes initiating, by the computing system, a simulation run associated with the simulated environment. The method includes, during the simulation run, obtaining, by the computing system, data indicative of a user input associated with a motion of the simulated object within the simulated environment. The method includes, in response to the user input and during the simulation run, controlling, by the computing system, the motion of the simulated object within the simulated environment based at least in part on the data indicative of the user input. The method also includes controlling the simulated autonomous vehicle within the simulated environment.

Abstract: Systems and methods are directed to compensating for time delays. In one example, a system includes one or more processors and memory including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining first pose data indicative of a pose of a vehicle; obtaining first control data indicative of a first vehicle control command that has yet to affect control of the vehicle; determining, based at least partially on the first pose data and the first control data, predicted pose data indicative of an estimate of a pose of the vehicle that will result after the vehicle control command affects control of the vehicle; and generating, based at least partially on the predicted pose data, second control data indicative of a second vehicle control command to be applied subsequent to the first vehicle control command.

Abstract: Systems and methods are directed to monitoring the status of a vehicle controller or other autonomy system during operation of an autonomous vehicle. In one example, a system includes one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining a message from a vehicle controller. The operations further include, based at least partly on the message, determining whether a failure mode exists. The operations further include providing, in response to determining the failure mode exists, one or more commands to implement a safety measure response for the autonomous vehicle.