A robot control system according to an embodiment is configured to control a mobile robot configured to autonomously move by referring to a map, the robot control system being further configured to: acquire a distance to a nearby object measured by using a range sensor; specify a position of the nearby object on the map according to the distance from a position of the mobile robot to the nearby object; estimate a movement vector indicating a moving speed and a moving direction of the nearby object according to a change in the distance to the nearby object; add a cost for restricting a movement of the mobile robot on the map; and perform control so that the mobile robot moves according to the cost updated according to a result of measurement by the range sensor.

A robot control system according to an embodiment is configured to control a mobile robot configured to autonomously move by referring to a map, the robot control system being further configured to: acquire a distance to a nearby object measured by using a range sensor; specify a position of the nearby object on the map according to the distance from a position of the mobile robot to the nearby object; estimate a movement vector indicating a moving speed and a moving direction of the nearby object according to a change in the distance to the nearby object; add a cost for restricting a movement of the mobile robot on the map; and perform control so that the mobile robot moves according to the cost updated according to a result of measurement by the range sensor.

A robotic system that includes a mobile robot linked to a plurality of remote stations. One of the remote stations includes an arbitrator that controls access to the robot. Each remote station may be assigned a priority that is used by the arbitrator to determine which station has access to the robot. The arbitrator may include notification and call back mechanisms for sending messages relating to an access request and a granting of access for a remote station.

Patient support apparatuses, such as beds, cots, stretchers, recliners, or the like, include control systems with one or more image, radar, and/or laser sensors to detect objects and determine if a likelihood of collision exists. If so, the control system controls the speed and steering of the patient support apparatus in order to reduce the likelihood of collision. The control system may be adapted to autonomously drive the patient support apparatus, to transmit a message to a remote device indicating whether it is occupied by a patient or not, and/or to transmit its route to the remote device. The remote device may determine an estimate of a time of arrival of the patient support apparatus at a particular destination and/or determine a distance of the patient support apparatus from the particular destination.

The invention relates to a special controller for an electric wheelchair (D), comprising an element for inputting commands (input element) and an adapter box (B) for transmitting data of the input element to an input/output module (C) of the electric wheelchair (D), wherein the data of the input element are transmittable wirelessly to the adapter box (B) and the input element comprising a wearable computer system (wearable) (A).

An embodiment relates to an omnidirectional chassis for a gantry of a computed tomography device. The omnidirectional chassis includes a first pair of omnidirectional wheels; and a first wheel suspension for the first pair of omnidirectional wheels. The first wheel suspension includes a connecting unit to connect the first wheel suspension to a rack; a swivel unit connected to the connecting unit via a first swivel bearing and swivel-mounted about a first swivel axis relative to the connecting unit; and a tandem unit, connected to the swivel unit via a second swivel bearing and swivel-mounted about a second swivel axis. In an embodiment, the first pair of omnidirectional wheels is coupled to the tandem unit such that, on a swivel movement of the tandem unit about the second swivel axis, one omnidirectional wheel of the first pair of omnidirectional wheels is relatively raised and another omnidirectional wheel is relatively lowered.

Methods, systems, and apparatus for an automated platform system. The automated platform system includes a docking station and a personal device connected to an automated robot platform. The automated robot platform includes one or more arms and an adjustable platform surface. The automated robot platform includes one or more imaging devices configured to receive imaging feedback and one or more transportation components coupled to the base. The one or more transportation components are configured to move in multiple directions. The automated robot platform includes one or more data processors that are configured to obtain imaging feedback. The one or more data processors are configured to operate the one or more transportation components to move in multiple directions to a first location based on the imaging feedback, and adjust the adjustable platform surface to a first height and a first angle.

A system and method for a motorized mobile chair use a plurality of sensors having a plurality of sensor types to detect a plurality of objects and generate sensor data about the detected objects, each of the detected objects being a person, the sensor data about the objects comprising a plurality of range measurements to the people and a plurality of bearing measurements to the people. The system has at least one processor to receive the sensor data about the people, group the detected people into a plurality of zones, determine a closest person in each zone, and generate one or more control signals to cause the motorized mobile chair to match a speed and a direction of the closest person in the zone corresponding to a direction of travel of the motorized mobile chair while at least approximately maintaining a selected space to the closest person in the zone corresponding to the direction of travel of the motorized mobile chair.

A method for constraining movements of a robot comprises: using the robot, receiving dynamic building data that describes a temporary condition of a building or campus comprising a set of buildings and a location of the temporary condition; using the robot, updating, from the dynamic building data, a map layer of a plurality of map layers of a map by calculating an increased cost of navigation of the portion of the map layer corresponding to the location of the temporary condition, the increased cost based on the description of the temporary condition; using the robot, upon receiving a task having an origin location and a destination location, determining a fastest route from the origin location to the destination location from the plurality of map layers of the map using a graph search algorithm that calculates an expected velocity of the robot over the portion of the map layer corresponding to the location of the temporary condition; using the robot, traversing the fastest route from the origin location to the destination location.

A robot includes: a communicator; a driver configured to drive the robot; at least one memory configured to store at least one instruction; and at least one processor configured to execute the at least one instruction to: receive first driving data from an external device in communication with the robot through the communicator and store the first driving data in the memory, control the driver to perform an operation based on the first driving data, identify, based on an error in communication connection between the robot and the external device occurring, second driving data received by the robot from the external device within a threshold period based on a point in time at which the error in communication connection occurs, wherein the second driving data matches with at least a portion of the first driving data, identify third driving data that is at least a portion of the first driving data and is consecutive to the portion of the first driving data that matches with the second driving data, and control the driver to perform an operation after the point in time at which the error in communication connection between the robot and the external device occurs based on the third driving data.