A system includes a robotic vehicle having a propulsion and a manipulator configured to perform designated tasks. The system also including a local controller disposed onboard the robotic vehicle and configured to receive input signals from an off-board controller. Responsive to receiving an input signal for moving in an autonomous mode, the local controller is configured to move the robotic vehicle toward one of the different final destinations by autonomously and iteratively determining a series of waypoints until the robotic vehicle has reached the one final destination. For each iteration, the local controller is configured to determine a next waypoint between a current location of the robotic vehicle and the final destination, determine movement limitations of the robotic vehicle, and generate control signals in accordance with the movement limitations.

An autonomous vehicle can classify and prioritize agent of interest (AOI) objects located around the autonomous vehicle to manage computational resources. An example method performed by an autonomous vehicle includes determining, based on a location of the autonomous vehicle and based on a map, an area in which the autonomous vehicle is operated, determining, based on sensor data received from sensors located on or in the autonomous vehicle, attributes of objects located around the autonomous vehicle, where the attributes include information that describes a status of the objects located around the autonomous vehicle, selecting, based at least on the area, a classification policy that includes a plurality of rules that are associated with a plurality of classifications to classify the objects, and for each of the objects located around the autonomous vehicle: monitoring an object according to a classification of the object based on the classification policy.

Provided is a medium storing instructions that when executed by one or more processors of a robot effectuate operations including: obtaining, with a processor, first data indicative of a position of the robot in a workspace; actuating, with the processor, the robot to drive within the workspace to form a map including mapped perimeters that correspond with physical perimeters of the workspace while obtaining, with the processor, second data indicative of displacement of the robot as the robot drives within the workspace; and forming, with the processor, the map of the workspace based on at least some of the first data; wherein: the map of the workspace expands as new first data of the workspace are obtained with the processor; and the robot is paired with an application of a communication device.

A method for constraining robot autonomy language includes receiving a navigation command to navigate a robot to a mission destination within an environment of the robot and generating a route specification for navigating the robot from a current location in the environment to the mission destination in the environment. The route specification includes a series of route segments. Each route segment in the series of route segments includes a goal region for the corresponding route segment and a constraint region encompassing the goal region. The constraint region establishes boundaries for the robot to remain within while traversing toward the goal region. The route segment also includes an initial path for the robot to follow while traversing the corresponding route segment.

A method for constraining robot autonomy language includes receiving a navigation command to navigate a robot to a mission destination within an environment of the robot and generating a route specification for navigating the robot from a current location in the environment to the mission destination in the environment. The route specification includes a series of route segments. Each route segment in the series of route segments includes a goal region for the corresponding route segment and a constraint region encompassing the goal region. The constraint region establishes boundaries for the robot to remain within while traversing toward the goal region. The route segment also includes an initial path for the robot to follow while traversing the corresponding route segment.

A cleaning system and a cleaning method are provided. The cleaning system includes a main body, an air suctioning device, a light source, an optical sensor, a memory and a processing unit. The air suctioning device includes an air flow passage and a fan-motor assembly that is disposed in the air flow passage and generates a suction force to suction outside air through the air flow passage. The light source emit light to the air flow passage. The optical sensor captures a plurality of successive image frames from the air flow passage. The processing unit is configured to: obtain first and second image frames from the successive image frames; compare the first image frame with the second image frame to identify dust particles; obtain a particle feature of the dust particles; and determine a current cleanness condition according to the particle feature.

A method for constructing a map for a mower includes: acquiring a preliminary map of a work region, two adjacent target points are used as first target points and are connected to form an initial connecting line; selecting a target point farthest from the initial connecting line as a second target point, and using a connecting line between the second target point and the first target points as to-be-processed connecting lines; selecting a third target point for each to-be-processed connecting line; when a condition is met, using connecting lines between the third target point and the target points at the two ends of the to-be-processed connecting line as new to-be-processed connecting lines and returning; retaining each of the third target points whose distance from a corresponding to-be-processed connecting line is greater than the first preset threshold as a map construction target point, and constructing a boundary map.

An in-vehicle system for generating precise, lane-level road map data includes a GPS receiver operative to acquire positional information associated with a track along a road path. An inertial sensor provides time local measurement of acceleration and turn rate along the track, and a camera acquires image data of the road path along the track. A processor is operative to receive the local measurement from the inertial sensor and image data from the camera over time in conjunction with multiple tracks along the road path, and improve the accuracy of the GPS receiver through curve fitting. One or all of the GPS receiver, inertial sensor and camera are disposed in a smartphone. The road map data may be uploaded to a central data repository for post processing when the vehicle passes through a WiFi cloud to generate the precise road map data, which may include data collected from multiple drivers.

A method of controlling movement of a robotic cleaning device over an area to be cleaned. The method includes storing at least one representation of the area over which the robotic cleaning device is to move, receiving an instruction to execute a cleaning program, localizing, in response to the instruction, the robotic cleaning device relative to the stored representation, and moving over the area to be cleaned as stipulated by the cleaning program by taking into account the stored representation.

A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.