Abstract: Some aspects include a method including: generating, with a processor of the robot, a map of the workspace; segmenting, with the processor of the robot, the map into a plurality of zones; transmitting, with the processor of the robot, the map to an application of a communication device; receiving, with the application, the map; displaying, with the application, the map; receiving, with the application, at least one input for the map; implementing, with the application, the at least one input into the map to generate an updated map of the workspace; transmitting, with the application, the updated map to the processor of the robot; receiving, with the processor of the robot, the updated map; generating, with the processor of the robot, a movement path based on the map or the updated map; and actuating, with the processor of the robot, the robot to traverse the movement path.

Abstract: Included is a method for collaboration between a first robotic chassis and a second robotic chassis, including: executing, with the processor of the first robotic chassis, a first part of a task; transmitting, with the processor of the first robotic chassis, a signal to a processor of the second robotic chassis upon completion of the first part of the task; and executing, with the processor of the second robotic chassis, a second part of the task upon receiving the signal transmitted from the processor of the first robotic chassis; wherein the first robotic chassis and the second robotic chassis provide differing services.

Abstract: Provided is a method including emitting, with a laser light emitter disposed on a robot, a collimated laser beam projecting a light point on a surface opposite the laser light emitter; capturing, with each of at least two image sensors disposed on the robot, images of the projected light point; overlaying, with a processor of the robot, the images captured by the at least two image sensors to produce a superimposed image showing both captured images in a single image; determining, with the processor of the robot, a first distance between the projected light points in the superimposed image; and determining, with the processor, a second distance based on the first distance using a relationship that relates distance between light points with distance between the robot or a sensor thereof and the surface on which the collimated laser beam is projected.

Abstract: Included is a method of path planning for a robotic device, including: receiving, by a processor of the robotic device, a sequence of one or more commands; executing, via the robotic device, the sequence of one or more commands; saving the sequence of one or more commands in memory of the robotic device after a predetermined amount of time from receiving a most recent one or more commands; and re-executing the saved sequence of one or more commands.

Abstract: Provided is an autonomous hospital bed including: a frame; wheels; motors to drive the wheels; a controller in communication with the motors; sensors; a processor; a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuate operations including: capturing, with the sensors, depth data indicating distances to objects within an environment of the hospital bed and directions of the distances; capturing, with the sensors, movement data indicating movement distance and direction of the hospital bed; generating, with the processor, a map of the environment using the depth and movement data; generating, with the processor, a movement path to a first location; instructing, with the processor, motor drivers of the wheels to move the hospital bed along the movement path; and, inferring, with the processor, a location of the hospital bed within the environment as the hospital bed navigates along the movement path.

Abstract: Provided is a method for operating a robot, including capturing images of a workspace, comparing at least one object from the captured images to objects in an object dictionary, identifying a class to which the at least one object belongs using an object classification unit, instructing the robot to execute at least one action based on the object class identified, capturing movement data of the robot, and generating a planar representation of the workspace based on the captured images and the movement data, wherein the captured images indicate a position of the robot relative to objects within the workspace and the movement data indicates movement of the robot.

Abstract: Provided is a method for navigating and mapping a workspace, including: obtaining a stream of spatial data indicative of a robot's position in a workspace, the stream of spatial data being based on at least output of a first sensor; obtaining a stream of movement data indicative of the robot's displacement in the workspace, the stream of movement data being based on at least output of a second sensor of different type than the first sensor; navigating along a path of the robot in the workspace based on the stream of spatial data; while navigating, mapping at least part of the workspace based on the stream of spatial data to form or update a spatial map in memory; and switching to a second mode of operation if the stream of spatial data is unavailable due to the first sensor becoming impaired or inoperative.

Abstract: A tangible, non-transitory, machine readable medium storing instructions that when executed by an image processor effectuates operations including: causing the camera to capture one or more images of an environment of the robotic device; receiving, with the image processor, one or more multidimensional arrays including at least one parameter that describes a feature included in the one or more images, wherein values of the at least one parameter correspond with pixels of a corresponding one or more images of the feature; determining, with the image processor, an amount of asymmetry of the feature in the one or more images based on at least a portion of the values of the at least one parameter; and, transmitting, with the image processor, a signal to the processor of the controller to adjust a heading of the robotic device by an amount proportional to the amount of asymmetry of the feature.

Abstract: Provided is a method for operating a robot, including capturing images of a workspace, comparing at least one object from the captured images to objects in an object dictionary, identifying a class to which the at least one object belongs using an object classification unit, instructing the robot to execute at least one action based on the object class identified, capturing movement data of the robot, and generating a planar representation of the workspace based on the captured images and the movement data, wherein the captured images indicate a position of the robot relative to objects within the workspace and the movement data indicates movement of the robot.

Abstract: Provided is a process executed by a robot, including: traversing, to a first position, a first distance in a backward direction; after traversing the first distance, rotating 180 degrees in a first rotation; after the first rotation, traversing, to a second position, a second distance in the second direction; and after traversing the second distance, rotating 180 degrees in a second rotation such that the field of view of the sensor points in the first direction.

Abstract: Provided is a method including capturing, by an image sensor disposed on a robot, images of a workspace; obtaining, by a processor of the robot or via the cloud, the captured images; comparing, by the processor of the robot or via the cloud, at least one object from the captured images to objects in an object dictionary; identifying, by the processor of the robot or via the cloud, a class to which the at least one object belongs using an object classification unit; and instructing, by the processor of the robot, the robot to execute at least one action based on the object class identified.

Abstract: Provided is a method including capturing, by an image sensor disposed on a robot, images of a workspace; obtaining, by a processor of the robot or via the cloud, the captured images; comparing, by the processor of the robot or via the cloud, at least one object from the captured images to objects in an object dictionary; identifying, by the processor of the robot or via the cloud, a class to which the at least one object belongs using an object classification unit; and instructing, by the processor of the robot, the robot to execute at least one action based on the object class identified.

Abstract: Provided is a process that includes: obtaining a first version of a map of a workspace; selecting a first undiscovered area of the workspace; in response to selecting the first undiscovered area, causing the robot to move to a position and orientation to sense data in at least part of the first undiscovered area; and obtaining an updated version of the map mapping a larger area of the workspace than the first version.

Abstract: A robotic surface cleaning device is provided, including a casing, a chassis, a set of wheels coupled to the chassis to drive the robotic surface cleaning device, a control system to instruct movement of the set of wheels, a battery to provide power to the robotic surface cleaning device, one or more sensors, a processor, rotating assembly, including a plate supported by a base of the casing, rotating mechanism to rotate the plate; and one or more cleaning apparatuses mounted to a first side of the plate.

Abstract: Techniques for minimizing redundancy of surface coverage of a workspace by a robotic device are presented, the techniques including: obtaining, with one or more processors of a robot, a map of a workspace, the map quantizing the workspace into a plurality of cells, each cell corresponding to an area of the workspace; segmenting, with the one or more processors of the robot, the workspace into a plurality of zones, each zone having a subset of the plurality of cells; determining, with the one or more processors of the robot, a sequence of the zones among a plurality of candidate sequences based on an effect of the sequence on a cost of a cost function that is based on travel distance of the robot through the sequence; and causing, with the one or more processors of the robot, the robot to traverse the zones in the determined sequence.

Abstract: Provided is a process, including: obtaining, with one or more processors, first depth data, wherein: the first depth data indicates a first distance from a robot at a first position to a surface of, or in, a workspace in which the robot is disposed, the first depth data indicates a first direction in which the first distance is measured, the first depth data indicates the first distance and the first direction in a frame of reference of the robot, and the frame of reference of the robot is different from a frame of reference of the workspace; translating, with one or more processors, the first depth data into translated first depth data that is in the frame of reference of the workspace; and storing, with one or more processors, the translated first depth data in memory.

Abstract: Provided is a process executed by a robot, including: traversing, to a first position, a first distance in a backward direction; after traversing the first distance, rotating 180 degrees in a first rotation; after the first rotation, traversing, to a second position, a second distance in the second direction; and after traversing the second distance, rotating 180 degrees in a second rotation such that the field of view of the sensor points in the first direction.

Abstract: Provided is a process that includes: obtaining a first version of a map of a workspace; selecting a first undiscovered area of the workspace; in response to selecting the first undiscovered area, causing the robot to move to a position and orientation to sense data in at least part of the first undiscovered area; and obtaining an updated version of the map mapping a larger area of the workspace than the first version.

Abstract: Provided is a process, including: obtaining, with one or more processors, first depth data, wherein: the first depth data indicates a first distance from a robot at a first position to a surface of, or in, a workspace in which the robot is disposed, the first depth data indicates a first direction in which the first distance is measured, the first depth data indicates the first distance and the first direction in a frame of reference of the robot, and the frame of reference of the robot is different from a frame of reference of the workspace; translating, with one or more processors, the first depth data into translated first depth data that is in the frame of reference of the workspace; and storing, with one or more processors, the translated first depth data in memory.

Abstract: Techniques for minimizing redundancy of surface coverage of a workspace by a robotic device are presented, the techniques including: obtaining, with one or more processors of a robot, a map of a workspace, the map quantizing the workspace into a plurality of cells, each cell corresponding to an area of the workspace; segmenting, with the one or more processors of the robot, the workspace into a plurality of zones, each zone having a subset of the plurality of cells; determining, with the one or more processors of the robot, a sequence of the zones among a plurality of candidate sequences based on an effect of the sequence on a cost of a cost function that is based on travel distance of the robot through the sequence; and causing, with the one or more processors of the robot, the robot to traverse the zones in the determined sequence.