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.

A mobile outdoor power equipment machine for performing a controlled task within a work area includes a drive system for providing movement of the machine, a working apparatus for performing the task, and a scanning system for scanning an area surrounding the machine. The scanning system is configured to provide detection of physical elements in the environment to aid in navigation of the machine. In an embodiment, the scanning system and a control system are configured to scan the area, determine the presence of a physical element in the area, determine that the physical element is located within the work area, determine the proximity of the physical element to the machine, and direct a behavior of the machine.

An unmanned aerial vehicle (UAV) or drone executes a neural network to assist with detecting and responding to attacks. The neural network may monitor, in real time, the data stream from a plurality of onboard sensors during navigation and may communicate with a high-altitude pseudosatellite (HAPS) platform. For example, if the neural network detects a cyber-attack but determines that it does not interfere with external communications, it may shift navigation control of the drone to the HAPS.

Improved mobile robots and systems and methods thereof, described herein, can enhance security and monitoring services of grounds and property. And, such mobile robots and systems and methods thereof can enhance policing as well as customer service and help desk functionality. In some embodiments, the mobile robots and systems and methods thereof can enhance exploration, such as space exploration.

The information processing apparatus includes an extraction unit configured to extract at least one first photographed image, the first photographed image being similar to a second photographed image which is photographed by using a second photographing apparatus mounted on a moving apparatus, the moving apparatus being moving in a predetermined region, from a plurality of first photographed images which are photographed by using a first photographing apparatus for creating a three-dimensional image of the predetermined region, an estimation unit configured to estimate a first photographing orientation of the first photographing apparatus, the first photographing apparatus photographing the first photographed image which is extracted, and a second photographing orientation of the second photographing apparatus at a time when the second photographed image is photographed, and a control unit configured to control an action of the moving apparatus based on the first photographing orientation and the second photographing orientation.

An autonomous running vehicle transmits a camera image around the vehicle photographed by a camera to a remote monitoring center. An obstacle is detected on the basis of information obtained from autonomous sensors including the camera. When an obstacle is detected, the autonomous running vehicle is automatically stopped. The remote monitoring center determines, when the autonomous running vehicle automatically stops, whether or not the run of the autonomous running vehicle is permitted to restart on the basis of the received camera video. When it is determined that the autonomous running vehicle can be restarted, a departure signal is transmitted to the autonomous running vehicle. When the departure signal is received from the remote monitoring center, the autonomous running vehicle restarts running.

There is provided a smart detection system including multiple sensors and a central server. The central server confirms a model of every sensor and a position thereof in an operation area. The central server confirms an event position and predicts a user action according to event signals sent by the multiple sensors.

A configuration is described that is capable of determining a target landing position of a drone according to a sentence indicating a landing position generated by a user. Aspects including identifying an object type of an object contained in a captured image of a camera mounted on a mobile body; sentence analysis processing analyzes a sentence indicating a designated arrival position; word-corresponding subject selection processing collates results of the sentence analysis processing with the object identification processing and selecting a subject corresponding to a word included in the sentence indicating the designated arrival position from the captured image; and target arrival position determination processing extracts an area corresponding to the designated arrival position indicated by the sentence indicating the designated arrival position from the captured image on the basis of a result of word-corresponding subject selection processing, and area determination is made as target arrival position of mobile body.

A configuration is described that is capable of determining a target landing position of a drone according to a sentence indicating a landing position generated by a user. Aspects including identifying an object type of an object contained in a captured image of a camera mounted on a mobile body; sentence analysis processing analyzes a sentence indicating a designated arrival position; word-corresponding subject selection processing collates results of the sentence analysis processing with the object identification processing and selecting a subject corresponding to a word included in the sentence indicating the designated arrival position from the captured image; and target arrival position determination processing extracts an area corresponding to the designated arrival position indicated by the sentence indicating the designated arrival position from the captured image on the basis of a result of word-corresponding subject selection processing, and area determination is made as target arrival position of mobile body.

A domestic robotic system, for example for mowing the lawn, including a robot, which includes: a movement system having wheels or the like for moving the robot over a surface; an image obtaining device, such as a camera, for obtaining images of the exterior environment of the robot; and at least one processor in electronic communication with the movement system and the image obtaining device. The at least one processor is programmed to: detect a predetermined pattern within at least one of the images, with this predetermined pattern being associated with a marker provided on a base station; respond to the detection of the predetermined pattern by determining, by a first process, an estimate of the robot's position and/or orientation, this estimate of the robot's position and orientation being relative to the base station, the at least one processor and the image obtaining device thereby forming part of a first positioning system for the robot; determine, by a second process, an alternative estimate of the robot's position and/or orientation, the at least one processor thereby forming part of a second positioning system for the robot; and perform at least one calibration of the second positioning system using the first positioning system.