Provided is a robot for transporting patient treatment tools. The robot includes a main body providing a space open in a front side of the main body and capable of traveling on the ground; a communication unit installed in the main body and wirelessly connected to the call signal generator; a control unit located on an upper side of the main body and manipulated by a user; an elevating structure slidably installed in the space of the main body; elevating means for elevating the elevating structure; a storage box supported by the elevating structure, temporarily accommodating treatment tools introduced from the outside, being movable forwards and backwards, and moving forwards and opened to send the treatment tools to the outside; and a storage box driving unit for moving the storage box forwards and backwards.

An information processing system controls an autonomous traveling body capable of autonomously traveling on a learned route. The information processing system includes a route information storage unit to store suspension point information indicating a suspension point at which the autonomous traveling body has suspended autonomous traveling on a particular learned route, and an acquisition unit to acquire current position information indicating a current position of the autonomous traveling body according to an instruction to resume the autonomous traveling, and controls the autonomous traveling body to return to the particular route, based on at least the current position information and the suspension point information.

A mobile medical device is driven by a chassis. The movement is brought about, or at least supported by, at least one drive. A direction influencing device varies the direction of movement. Both the drive and the direction influencing device may be activated by a control device. End stations and paths leading to the end stations, as well as a current position of the device, are known to the control device. The control device accepts a drive request from an operator and establishes an at least approximate desired direction of the movement. The control device activates the drive while accepting the drive request and activates the direction influencing device to drive the device on one of the paths while accepting the drive request and while the current position of the device is approximately on the path. Furthermore, the control device continuously updates the position of the device during movement.

A communications platform to facilitate communication between patients and doctors in a remote setting using digital health robot is provided. The digital health robot includes measurement systems to simulate a live examination. A video Visit may be initiated at behest of the patient where doctors may review live results and provide direct feedback to patients.

The present disclosure describes various aspects of remote presence interfaces (RPIs) for use on portable electronic devices (PEDs) to interface with remote presence devices. An RPI may allow a user to interact with a telepresence device, view a live video feed, provide navigational instructions, and/or otherwise interact with the telepresence device. The RPI may allow a user to manually, semi-autonomously, or autonomously control the movement of the telepresence device. One or more panels associated with a video feed, patient data, calendars, date, time, telemetry data, PED data, telepresence device data, healthcare facility information, healthcare practitioner information, menu tabs, settings controls, and/or other features may be utilized via the RPI.

A control method in a control device that controls movement of a plurality of moving bodies includes: moving the plurality of moving bodies in accordance with movement plans that have been predetermined and defining one or more passageways where each of the plurality of moving bodies passes from a departure place to a destination; acquiring an actual delay time that is a delay time of each of the plurality of moving bodies, the delay time being generated in each of the one or more passageways; updating a model representing a length of the delay time defined for each of the one or more passageways using the actual delay time in a corresponding passageway among the one or more passageways; acquiring a current location of each of the plurality of moving bodies; and updating each of the movement plans based on the updated model, the destination, and the current location.

For a particularly precise check of travel accuracy, a measuring system is provided for checking and/or calibrating a travel accuracy of a mobile medical device that may be moved over a floor automatically or semiautomatically in a motorized manner. The measuring system includes a flat mat with an underside that may be arranged on the floor, and with an upper side on which indicator patterns that include at least one zero point mark for positioning the medical device and a number of track markings for travel motions of the mobile device are arranged. The measuring system includes a unit for illuminating the indicator patterns that are arranged on the mat using at least one concentrated light beam. The unit is arranged on the mobile medical device, such that the light beam is directed onto the upper side of the mat.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (AI) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (AI) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

A transport robot is configured to transfer a transported article to and from an installed shelf by passing the installed shelf. A shelf portion that holds the transported article is configured to pass the installed shelf by the transport robot traveling. A chassis is configured to support the shelf portion. A stand is disposed on a first end portion side in a right-left direction of the transport robot, and extends upward from the chassis. An operating unit is configured to be installed on the stand.