Abstract: A method in a navigational controller includes: obtaining (i) a plurality of task fragments identifying respective sets of sub-regions in a facility, and (ii) an identifier of a task to be performed by a mobile automation apparatus at each of the sets of sub-regions; selecting an active one of the task fragments according to a sequence specifying an order of execution of the task fragments; generating a path including (i) a taxi portion from a current position of the mobile automation apparatus to the sub-regions identified by the active task fragment, and (ii) an execution portion traversing the sub-regions identified by the active task fragment; during travel along the taxi portion, determining, based on a current pose of the mobile automation apparatus, whether to initiate execution of another task fragment; and when the determination is affirmative, updating the sequence to mark the other task fragment as the active task fragment.

Abstract: A navigational control method for a mobile automation apparatus includes: controlling a depth sensor to capture depth data representing a portion of a facility containing an obstacle; identifying the obstacle from the depth data; determining a probability that the obstacle is static; based on the probability, assigning the obstacle one of a dynamic class, a static class, and at least one intermediate class; updating a map to include a position of the obstacle, and the assigned class; and selecting, based on the assigned class, a navigational control action from a first action type associated with the dynamic class and the intermediate class, and a second action type associated with the static class.

Abstract: A method in a navigational controller includes: obtaining image data and depth data from corresponding sensors of a mobile automation apparatus; detecting an obstacle from the depth data and classifying the obstacle as one of a human obstacle and a non-human obstacle; in response to the classifying of the obstacle as the human obstacle, selecting a portion of the image data that corresponds to the obstacle; detecting, from the selected image data, a feature of the obstacle; based on a detected position of the detected feature, selecting an illumination control action; and controlling an illumination subsystem of the mobile automation apparatus according to the selected illumination control action.

Abstract: A method includes: selecting first control parameters for a perimeter intrusion detector of a mobile automation apparatus; controlling the perimeter intrusion detector according to the first control parameters, to monitor a first perimeter surrounding the mobile automation apparatus; determining that navigational data of the mobile automation apparatus defines a maneuver satisfying perimeter modification criteria; in response to determining that a likelihood of intrusion of the first perimeter associated with the maneuver exceeds a threshold, selecting second control parameters for the perimeter intrusion detector; modifying the first perimeter to a second perimeter according to the second control parameters; and controlling the perimeter intrusion detector to monitor the second perimeter.

Abstract: A method of obstacle handling for a mobile automation apparatus includes: obtaining an initial localization of the mobile automation apparatus in a frame of reference; detecting an obstacle by one or more sensors disposed on the mobile automation apparatus; generating and storing an initial location of the obstacle in the frame of reference, based on (i) the initial localization, and (ii) a detected position of the obstacle relative to the mobile automation apparatus; obtaining a correction to the initial localization of the mobile automation apparatus; and applying a positional adjustment, based on the correction, to the initial position of the obstacle to generate and store an updated position of the obstacle.

Abstract: A method of navigational ray casting in a computing device includes: obtaining a distance map having a plurality of cells representing respective sub-regions of an environment containing obstacles; wherein each cell defines a minimum obstacle distance indicating a distance from the corresponding sub-region to a nearest one of the obstacles; selecting an origin cell from the plurality of cells, and setting the origin cell as a current cell; selecting a ray cast direction for a ray originating from the origin cell; retrieving the minimum obstacle distance defined by the current cell; selecting a test cell at the minimum obstacle distance from the current cell in the ray cast direction; determining whether the test cell indicates the presence of one of the obstacles; and when the determination is affirmative, determining a total distance between the origin cell and the test cell.

Abstract: A mobile automation apparatus includes: a chassis supporting a locomotive assembly and an illumination assembly configured to emit light over a field of illumination (FOI); a navigational controller connected to the locomotive assembly and the illumination assembly, the navigational controller configured to: obtain a task definition identifying a region in a facility; generate a data capture path traversing the region from an origin location to a destination location, the data capture path including: (i) an entry segment beginning at the origin location and defining a direction of travel angled away from a support structure in the region such that a lagging edge of the FOI intersects with the support structure; and (ii) an exit segment defining a direction of travel angled towards the support structure and terminating at the destination location such that a leading edge of the FOI intersects with the support structure.

Abstract: A navigational control method for a mobile automation apparatus includes: controlling a depth sensor to capture depth data representing a portion of a facility containing an obstacle; identifying the obstacle from the depth data; determining a probability that the obstacle is static; based on the probability, assigning the obstacle one of a dynamic class, a static class, and at least one intermediate class; updating a map to include a position of the obstacle, and the assigned class; and selecting, based on the assigned class, a navigational control action from a first action type associated with the dynamic class and the intermediate class, and a second action type associated with the static class.

Abstract: A method in a navigational controller includes: obtaining image data and depth data from corresponding sensors of a mobile automation apparatus; detecting an obstacle from the depth data and classifying the obstacle as one of a human obstacle and a non-human obstacle; in response to the classifying of the obstacle as the human obstacle, selecting a portion of the image data that corresponds to the obstacle; detecting, from the selected image data, a feature of the obstacle; based on a detected position of the detected feature, selecting an illumination control action; and controlling an illumination subsystem of the mobile automation apparatus according to the selected illumination control action.

Abstract: A method for localization of a mobile automation apparatus includes, at a navigational controller: generating a set of candidate poses within an environmental map; updating the candidate poses according to motion data corresponding to movement of the mobile automation apparatus; receiving observational data collected at an actual pose of the mobile automation apparatus; generating (i) respective weights for the candidate poses, each weight indicating a likelihood that the corresponding candidate pose matches the actual pose, and (ii) a localization confidence level based on the weights; responsive to determining whether the localization confidence level exceeds a candidate pose resampling threshold: when the determination is affirmative, (i) increasing the candidate pose resampling threshold and (ii) generating a further set of candidate poses; and when the determination is negative, (i) decreasing the candidate pose resampling threshold without generating the further set; and repeating the updating, the rece

Abstract: A method of obstacle handling for a mobile automation apparatus includes: obtaining an initial localization of the mobile automation apparatus in a frame of reference; detecting an obstacle by one or more sensors disposed on the mobile automation apparatus; generating and storing an initial location of the obstacle in the frame of reference, based on (i) the initial localization, and (ii) a detected position of the obstacle relative to the mobile automation apparatus; obtaining a correction to the initial localization of the mobile automation apparatus; and applying a positional adjustment, based on the correction, to the initial position of the obstacle to generate and store an updated position of the obstacle.

Abstract: A method of navigational path planning for a mobile automation apparatus includes: obtaining an apparatus localization in a common frame of reference and a localization confidence level; detecting an obstacle boundary by one or more apparatus sensors; obtaining an obstacle map indicating the obstacle boundary in the frame of reference; generating a dynamic perimeter region of the obstacle boundary defining obstruction probabilities for respective distances from the obstacle boundary according to the localization confidence level; obtaining an environmental map indicating a predefined obstacle boundary; generating, for the predefined obstacle boundary, a static perimeter region defining obstructed space; identifying an obstructed portion of the dynamic perimeter region based on the obstruction probabilities and the apparatus localization; generating a navigational path traversing unobstructed space, that excludes the obstructed portion of the dynamic perimeter region, and the static perimeter region; and contr

Abstract: A method in a navigational controller includes: obtaining (i) a plurality of task fragments identifying respective sets of sub-regions in a facility, and (ii) an identifier of a task to be performed by a mobile automation apparatus at each of the sets of sub-regions; selecting an active one of the task fragments according to a sequence specifying an order of execution of the task fragments; generating a path including (i) a taxi portion from a current position of the mobile automation apparatus to the sub-regions identified by the active task fragment, and (ii) an execution portion traversing the sub-regions identified by the active task fragment; during travel along the taxi portion, determining, based on a current pose of the mobile automation apparatus, whether to initiate execution of another task fragment; and when the determination is affirmative, updating the sequence to mark the other task fragment as the active task fragment.

Abstract: A mobile automation apparatus includes: a chassis supporting a locomotive assembly and an illumination assembly configured to emit light over a field of illumination (FOI); a navigational controller connected to the locomotive assembly and the illumination assembly, the navigational controller configured to: obtain a task definition identifying a region in a facility; generate a data capture path traversing the region from an origin location to a destination location, the data capture path including: (i) an entry segment beginning at the origin location and defining a direction of travel angled away from a support structure in the region such that a lagging edge of the FOI intersects with the support structure; and (ii) an exit segment defining a direction of travel angled towards the support structure and terminating at the destination location such that a leading edge of the FOI intersects with the support structure.

Abstract: A computing device for generating a navigational path for a mobile automation apparatus includes: a memory storing, for each of a plurality of pairs of poses having predetermined orientations, a group of pre-computed path segments, each path segment traversing the pair of poses and corresponding to one of a set of entry poses and one of a set of exit poses; a navigational controller configured to: obtain a coarse path defined by a sequence of guide poses each having one of the predetermined orientations, the coarse path having a start location and an end location; for each successive pair of the guide poses, retrieve a selected one of the path segments from memory based on orientations of (i) the pair of guide poses, (ii) a preceding guide pose, and (iii) a following guide pose; and generate a final path for navigation by the apparatus by combining the selected path segments.

Abstract: A method of dynamic path generation in a navigational controller includes: generating (i) a plurality of paths extending from a starting location to a goal location, and (ii) a cost for each of the paths; selecting, based on the costs, an optimal path for execution from the plurality of paths; storing a subset of the costs in a cost history queue; responsive to detecting an obstacle during execution of the optimal path, retrieving one of the costs from the cost history queue; determining an initial re-planning search space based on the cost retrieved from the cost history queue; and initiating generation of a re-planned path within the initial re-planning search space.

Abstract: A method of controlling light emitters of a mobile automation apparatus includes: controlling a depth sensor to capture a plurality of depth measurements corresponding to an area containing a support structure; obtaining a support structure plane definition; selecting a subset of the depth measurements; determining, based on the subset of depth measurements and the support structure plane, whether the subset of the depth measurements indicates the presence of a sensitive receptor; when the determination is affirmative, disabling the light emitters; and when the determination is negative, controlling (i) the light emitters to illuminate the support structure and (ii) a camera to capture an image of the support structure simultaneously with the illumination.

Abstract: A method of controlling light emitters of a mobile automation apparatus includes: controlling a depth sensor to capture a plurality of depth measurements corresponding to an area containing a support structure; obtaining a support structure plane definition; selecting a subset of the depth measurements; determining, based on the subset of depth measurements and the support structure plane, whether the subset of the depth measurements indicates the presence of a sensitive receptor; when the determination is affirmative, disabling the light emitters; and when the determination is negative, controlling (i) the light emitters to illuminate the support structure and (ii) a camera to capture an image of the support structure simultaneously with the illumination.

Abstract: A method of navigational ray casting in a computing device includes: obtaining a distance map having a plurality of cells representing respective sub-regions of an environment containing obstacles; wherein each cell defines a minimum obstacle distance indicating a distance from the corresponding sub-region to a nearest one of the obstacles; selecting an origin cell from the plurality of cells, and setting the origin cell as a current cell; selecting a ray cast direction for a ray originating from the origin cell; retrieving the minimum obstacle distance defined by the current cell; selecting a test cell at the minimum obstacle distance from the current cell in the ray cast direction; determining whether the test cell indicates the presence of one of the obstacles; and when the determination is affirmative, determining a total distance between the origin cell and the test cell.

Abstract: A method for localization of a mobile automation apparatus includes, at a navigational controller: generating a set of candidate poses within an environmental map; updating the candidate poses according to motion data corresponding to movement of the mobile automation apparatus; receiving observational data collected at an actual pose of the mobile automation apparatus; generating (i) respective weights for the candidate poses, each weight indicating a likelihood that the corresponding candidate pose matches the actual pose, and (ii) a localization confidence level based on the weights; responsive to determining whether the localization confidence level exceeds a candidate pose resampling threshold: when the determination is affirmative, (i) increasing the candidate pose resampling threshold and (ii) generating a further set of candidate poses; and when the determination is negative, (i) decreasing the candidate pose resampling threshold without generating the further set; and repeating the updating, the rece