A robotic walking assistant includes a wheeled base having a base and one or more position adjustable wheels connected to the base, a body disposed in a vertical direction, positioned on the wheeled base and having a handle, and a control system that receives command instructions. Each of the one or more wheels is slidable with respect to the base between a retracted position and an extended position in a direction that is substantially parallel to a surface where the wheeled base moves. In response to the command instructions, the control system moves the one or more wheels between the retracted positions and the extended positions.

A control method for an electrical walker is provided. The control method includes measuring a plurality of slope angle values, determining a correction parameter value according to the plurality of slope angle values and generating a corrected driving force value according to the correction parameter value and an original driving force value.

Provided are an autonomous running device, a running control method for the autonomous running device, and a running control program of the autonomous running device that allow the autonomous running device to reach a destination while continuing estimation of its self-position. An autonomous running device includes a first position estimation unit that estimates the position of the autonomous running device on the basis of information about surroundings of the autonomous running device, produces information about the estimated position of the autonomous running device as first positional information, and updates the first positional information, a second position estimation unit that estimates the position of the autonomous running device on the basis of rotation amounts of wheels, produces information about the estimated position of the autonomous running device as second positional information, and updates the second positional information, and a control unit.

A method and systems for controlling and directing a means of transportation to autonomously navigate to a target location are provided. The method includes receiving measurements from one or more sensors of the means of transportation; building a route based on the measurement received for the means of transportation to navigate to a target location; generating localization estimation associated with the route built; generating a global path based on the route and the localization estimation; and performing local planning for directing the means of transportation to the target location while avoiding surrounding static or dynamic obstacles. The one or more sensors include a LiDAR sensor and an odometry sensor.

Navigation of a mobility aid robot having a camera and gripping part(s) disposed toward different directions is disclosed. The mobility aid robot is navigated to approach a user by identifying a posture of the user through the camera, determining a mode of the robot according to a type of the specified task to be performed on the user and the identified posture of the user, controlling the robot to move according to a planned trajectory corresponding to the determined mode of the robot, and turning the robot upon reaching the desired pose such that the gripping part faces the user, in response to the determined mode of the robot corresponding to the specified task of an assisting type and the user at one of a standing posture and a sitting posture.

Apparatus and methods for controlling a path of an autonomous mobile device based upon defining a series of origination positions and destination positions, each destination position correlating with position coordinates. A current position of an autonomous vehicle is determined via location automation such as real time communication systems and an approved pathway is generated to guide the autonomous vehicle. The position coordinates may be a set of values that accurately define a position in two dimensional 2D or three-dimensional (3D) space. Position coordinates may include cartesian coordinates.

The present disclosure provides a conveyance system and the like capable of preferably conveying a conveyed object in accordance with a state of the conveyed object. The conveyance system includes a conveyance robot, a drive controller, which is a controller, an image data acquisition unit, and a setting unit. The conveyance robot conveys the conveyed object. The drive controller controls an operation of the conveyance robot. The image data acquisition unit acquires image data obtained by capturing images of the conveyed object. The setting unit sets an operation parameter of the conveyance robot in the drive controller based on the acquired image data.

A plurality of thermal areas (11a, 11b, 11c, and 11d) of different thermal environments are formed in a room (11). When it is determined that a person (13) riding on a movable object (20) is feeling uncomfortable in the thermal area (11d), the movable object (20) is remotely operated to move toward the thermal area (11a) where the person (13) feels comfortable.

The invention discloses a system for controlling the movement of a personal mobility vehicle. The system includes a processing unit that receives and processes a location data of one or more obstacles over a period of time and determines a change frequency of change of location of the obstacles during the period of time and further generates a movement state categorization of the obstacles categorizing them into either a dynamic obstacle or a static obstacle. The processing unit further determines a dynamic distance traveled by the dynamic obstacle during the period of time and also determines the velocity of the dynamic obstacle. Further, based on the change frequency of change of location, the processing unit determines the movement probability data that relates to the probability of movement of a static obstacle. And, based on the velocity of dynamic obstacles during various time intervals of the time period, the processing unit determines the velocity prediction data which relates to the prediction of the velocity of a dynamic obstacle.

Methods are described that perform a dispatched consumer-to-store return or swap logistics operation for an item being replaced using a modular autonomous bot apparatus assembly and a dispatch server. The method begins with receiving a return operation dispatch command that includes identifier information, transport parameters, and designated pickup information for the item being replaced/returned, along with authentication information related to an authorized supplier of the item being replaced. Modular components of the bot apparatus are verified to be compatible with the dispatched logistics operation. The MAM then autonomously causes the bot apparatus to move to the designated pickup location, notifies the authorized supplier of an approaching pickup, receives supplier authorization input to permissively allow access to a payload area within the bot apparatus, monitors loading as the item being replaced is received along with return documentation, and then autonomously causes movement of the bot apparatus back to the origin location.