Abstract: Systems and methods for detecting, mapping, and route planning around cliffs for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot processing a three-dimensional range sensor scan may utilize pre-computed neighboring points to detect cliffs, navigable ramps, and holes in a plane of a map used by the robotic device to navigate.

Abstract: Systems and methods for systems and methods for real time calibration of multiple range sensors on a robot are disclosed herein. According to at least one non-limiting exemplary embodiment, methods for self-calibration are used to independently correct rotational errors in a pose of a sensor. In some instances, the self-calibration may further yield errors along at least one translational axis. According to at least one non-limiting exemplary embodiment, methods for cross-calibration are used to correct translational errors and to ensure all sensors on a robot agree on perceived locations of objects.

Abstract: Systems and methods for detecting, mapping, and route planning around cliffs for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot processing a three-dimensional range sensor scan may utilize pre-computed neighboring points to detect cliffs, navigable ramps, and holes in a plane of a map used by the robotic device to navigate.

Abstract: Systems and methods for detection of features within data collected by a plurality of robots by a centralized server are disclosed herein. According to at least one non-limiting exemplary embodiment, a plurality of robots may be utilized to collect a substantial amount of feature data using one or more sensors coupled thereto, wherein use of the plurality of robots to collect the feature data yields accurate localization of the feature data and consistent acquisition of the feature data. Systems and methods disclosed herein further enable a cloud server to identify a substantial number of features within the acquired feature data for purposes of generating insights. The substantial number of features far exceed a practical number of features of which a single neural network may be trained to identify.

Abstract: Systems and methods for data and confidentiality preservation for feature identification by robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a method for determining if an image depicts a human is disclosed. The determination may be utilized to either (i) censor the face of the human, or (ii) identify features within the image. The determination enhances feature identification by ensuring only uncensored and unobscured images are provided to one or more models for the identification to preserve human confidentiality.

Abstract: Systems and methods for training a robot to autonomously travel a route. In one embodiment, a robot can detect an initial placement in an initialization location. Beginning from the initialization location, the robot can create a map of a navigable route and surrounding environment during a user-controlled demonstration of the navigable route. After the demonstration, the robot can later detect a second placement in the initialization location, and then autonomously navigate the navigable route. The robot can then subsequently detect errors associated with the created map. Methods and systems associated with the robot are also disclosed.

Abstract: Systems, apparatuses, and methods for calibrating LiDAR sensors of a robot using intersecting LiDAR sensors are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may calibrate a calibration LiDAR based on a determined pose of the calibration LiDAR, wherein the pose is determined based on a measurement error between the calibration LiDAR and an intersecting reference LiDAR.

Abstract: Systems and methods for enhancing task performance and computer readable maps produced by robots using modular sensors is disclosed herein. According to at least one non-limiting exemplary embodiment, robots may perform a first set of tasks, wherein coupling one or more modular sensors to the robots may configure a robot to perform a second set of tasks, the second set of tasks includes the first set of tasks and at least one additional task.

Abstract: Systems and methods for robotic disinfection and sanitation of environments are disclosed herein. The robotic devices disclosed herein may detect and map locations of pathogens within environments. The robotic devices disclosed herein may utilize data from sensor units to sanitize objects using desired methods specified by operators. The robotic devices disclosed herein may sanitize environments comprising people.

Abstract: Systems and methods for editing routes for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, Bezier curves and controls are provided to enable a user to intuitively manipulate a robot route, including changing the shape of the route, deleting segments of the route, and/or adding new route segments.

Abstract: Systems, apparatuses, and methods for a distributed network of data collection and insight generation by server are disclosed herein. According to at least one non-limiting exemplary embodiment, the server may be configured to receive data from a network of data sources, receive an application from an application creator, and execute the application based on the data from the network of data sources to generate at least one insight, wherein the network of data sources may comprise mobile robots, stationary devices, IoT (Internet of Things) devices, and/or public data sources. The at least one insight may be utilized by robots to improve efficiency of operation or by humans to gain useful insights to the environment in which the data sources operate.

Abstract: Systems and methods for improved control of nonholonomic robotic systems are disclosed herein. According to at least one non-limiting exemplary embodiment, a holonomic reference point on or nearby a nonholonomic robot may be determined and utilized to navigate the robot along a target trajectory. Due to the holonomicity of the reference point, control logic of the robotic system may be greatly simplified, thereby enhancing accuracy of navigation and navigation capabilities of nonholonomic robotic systems.

Abstract: Systems, apparatuses, and methods for reducing network bandwidth usage by a fleet of robots. According to at least one non-limiting exemplary embodiment, robots coupled to a server collect and produce a substantial amount of data, only a portion of that data being useful for operators to monitor behavior of the robot. The present disclosure provides for, inter alia, optimized systems, apparatuses, and methods for operators to extract the useful data using only reduced bandwidth of cellular LTE networks or Wi-Fi networks.

Abstract: Systems and methods for optimizing robotic route planning are disclosed in relation to autonomous navigation of sharp turns, narrow passageways, and/or a sharp turn into a narrow passageway. Robots navigating a route comprising any of the above run the risk of colliding with environment obstacles when executing these maneuvers. Accordingly, systems and methods for improving robotic route planning are necessary within the art and are disclosed herein.

Abstract: Systems and methods for quantitatively measuring wheel slippage in differential drive robots are disclosed herein. According to at least one non-limiting exemplary embodiment, data from wheel encoders is compared to data from a gyroscope during execution of at least one of two tests disclosed herein to produce a quantitative value proportional to wheel slippage due to a differential drive robot rotating or turning.

Abstract: Systems and methods for laser and imaging odometry for autonomous robots are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may utilize images captured by a sensor and encoded with a depth parameter to determine its motion and localize itself. The determined motion and localization may then be utilized to verify calibration of the sensor based on a comparison between motion and localization data based on the images and motion and localization data based on data from other sensors and odometry units of the robot.

Abstract: Systems and methods for calibrating sensors of a robot are disclosed. In one exemplary implementation, an environment comprising a plurality of sensor targets and a fixed position for a robot allows for faster, more accurate calibration of a robot's sensors.

Abstract: Systems and methods for detection of features within data collected by a plurality of robots by a centralized server are disclosed herein. According to at least one non-limiting exemplary embodiment, a plurality of robots may be utilized to collect a substantial amount of feature data using one or more sensors coupled thereto, wherein use of the plurality of robots to collect the feature data yields accurate localization of the feature data and consistent acquisition of the feature data. Systems and methods disclosed herein further enable a cloud server to identify a substantial number of features within the acquired feature data for purposes of generating insights. The substantial number of features far exceed a practical number of features of which a single neural network may be trained to identify.

Abstract: Systems and methods for removing false positives from sensor detection for robotic apparatuses traveling a route, wherein the robot may use a material filter, digital filter, or a combination of digital and material filters of increasing strength to remove a false positive from sensor detection. After removing the false positive, signals to one or more motors coupled to the robot may configure the robotic to travel past the false positive along the route.

Abstract: Systems and methods for calibrating a robot's sensors are disclosed. In one exemplary implementation, an environment comprising a plurality of sensor targets and a fixed position for a robot allows for faster, more accurate calibration of a robot's sensors.