Zebra Technologies Corporation

Symbol Technologies, LLC

Peter Arandorenko

Sadegh Tajeddin

Melonee Wise

Harsoveet Singh

Bradley M Scott

Thomas D Kingsford

Kevin C Jen

Zi Cong Guo

Benjamin Narin

Chengzhi W Liu

Achal Dasa Arvind

Vaibhav K Bhilare

Asma Azim

A method includes: obtaining a pose of a mobile computing device associated with a worker in a facility; detecting a trigger event to initiate presentation, at the mobile computing device, of visual guidance corresponding to one of a plurality of mobile robots in the facility; in response to detecting the trigger event, selecting one of the mobile robots; determining, based on the pose of the mobile computing device and a map of the facility, whether the selected one of the mobile robots is visually obstructed from the pose of the mobile computing device; and when the selected one of the mobile robots is visually obstructed, providing visual guidance via the mobile computing device, the visual guidance indicating a current location of the selected mobile robot behind an obstruction.

Visual guidance for locating obstructed mobile robots

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.

Object classification for autonomous navigation systems

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.

Method, system and apparatus for localization-based historical obstacle handling

Obstacle detection for a mobile automation apparatus is provided. The mobile automation apparatus includes a structured light camera positioned on a support structure to detect at least a top of a shopping cart in a region adjacent to the mobile automation apparatus. The mobile automation apparatus can include other structured light cameras. Furthermore, one or more ultrasound arrays are used as secondary obstacle detector such that when the one or more ultrasound arrays detect an object, and at least one structured light camera simultaneously does not detect the object, an obstacle avoidance protocol is implemented.

Obstacle detection for a mobile automation apparatus

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 controlling the apparatus to traverse the generated navigational path.

Method, system and apparatus for obstacle handling in navigational path generation

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Mississauga, Canada

Peter Arandorenko