This automated analysis support robot for carrying out an inspection of an analysis module that automatically analyzes a biological sample comprises a vehicle body, a camera mounted on the vehicle body, a communication device which communicates directly or indirectly with the analysis module, and a computer for controlling the vehicle body and the camera, wherein the computer: controls the vehicle body to move to a predetermined operating position and to face an inspection target provided in the analysis module; images the inspection target using the camera; and processes a video of the inspection target to calculate management data relating to the inspection target.

A collection device includes an acquisition device, a control device, and a detection device. The acquisition device acquires information inside a space of a target region. The control device sets a detection path for a collection device based on an unreachable region within the space of the target region. The detection device acquires environmental data including environmental data of the unreachable region detected when the collection device moves along the detection path in the space of the target region.

A system and method is disclosed for configuring a group of mobile field devices using a configuration device (an HMI) is provided. In particular, the HMI is programmed to configure identically programmed field devices that are arbitrarily arranged in an application-dependent formation by defining and providing configuration parameters to the devices via wired and/or wireless communication. In particular, the HMI assigns a unique identifier to respective robots as a function of the position of the robot within the formation or the layout of the environment. Accordingly each robot can be efficiently configured by the HMI to operate independently yet as a coordinated member of the group and without requiring the robots to be placed in specific positions during the initial deployment. This obviates the need for constant independent control commands for each robot by a central controller or providing a customized control program to each robot during deployment.

Method for monitoring industrial safety, which includes: setting a field feature related to a working event and an industrial safety feature related to an industrial safety event. Controlling a self-propelled device to move within a working environment while also controlling an image capturing unit to capture an environmental image of the working environment, and controlling an internal computer to analyze the environmental image. Controlling the self-propelled device to stay at a location where the field feature is captured when the environmental image is analyzed and it was determined that the field feature exists in the working environment; and controlling the self-propelled device to transmit an industrial safety information related to the industrial safety event to the terminal device when the analysis of the captured environmental image indicates that the industrial safety feature exists in the field feature, thereby helping the industrial safety personnel to realize the on-site situation remotely.

An unmanned vehicle management system according to an aspect includes: a collection unit configured to collect video data acquired by an unmanned vehicle and natural disaster data related to natural disasters from information sources; a storage unit configured to store the video data and the natural disaster data; an analysis unit configured to extract feature amounts of the video data and the natural disaster data, and predict a high-risk area where a risk of natural disaster occurrence is higher than in other areas; a prediction unit configured to compare the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predict a disaster occurrence area where a disaster will occur; and a deployment unit configured to determine deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area.

An agricultural autonomous vehicle is provided which is operable to traverse a field and perform one or more detection tasks.

A method to perform measurements of a field is disclosed. The method includes disposing a landing dock at a target location in the field, the landing dock being coupled to a fiber optic cable for distributed fiber-optic sensing measurement, directing an unmanned aerial vehicle (UAV) to land on the landing dock, the UAV including an interrogator unit, communicatively coupling, in response to the UAV landing on the landing dock, the interrogator unit and the fiber optic cable, sending, by the interrogator unit, a light pulse to the fiber optic cable, receiving, by the interrogator unit and in response to sending the light pulse, a backscattered light signal from the fiber optic cable, and generating, by the interrogator unit and based on the received backscattered light signal, a measurement of the target location.

An agricultural autonomous vehicle is provided which is operable to traverse a field and perform one or more detection tasks.

An agricultural autonomous vehicle is provided which is operable to traverse a field and perform one or more detection tasks.

An un-manned aerial vehicle (UAV) for use in mitigation air pollution is provided. The UAV may include a filter system that draws in ambient air and passes the ambient air through a particulate filter to clean the air. The UAV may travel to a first location within an area of interest that needs to be cleaned. The UAV may then move to a second location that is a predetermined distance from the first location in x, y, or z directions. The UAV may further determine a first particulate matter measurement at the second location and determine a third location within the area of interest based on the first particulate matter measurement and the first location. The UAV may then determine a second particulate matter measurement at the third location and initiate a filtration process based on the first particulate matter measurement and the second particulate matter measurement.