Disclosed are a brain-computer interface based robotic arm self-assisting system and method. The system comprises a sensing layer, a decision-making layer and an execution layer. The sensing layer comprises an electroencephalogram acquisition and detection module and a visual identification and positioning module and is used for analyzing and identifying the intent of a user and identifying and locating positions of a corresponding cup and the user's mouth based on the user intent. The execution layer comprises a robotic arm control module that performs trajectory planning and control for a robotic arm based on an execution instruction received from a decision-making module. The decision-making layer comprises the decision-making module that is connected to the electroencephalogram acquisition and detection module, the visual identification and positioning module and the robotic arm control module to implement the acquisition and transmission of data of an electroencephalogram signal, a located position and a robotic arm status and the sending of the execution instruction for the robotic arm. The system combines the visual identification and positioning technology, a brain-computer interface and a robotic arm to facilitate paralyzed patients to drink water by themselves, improving the quality of life of the paralyzed patients.

Disclosed are a brain-computer interface based robotic arm self-assisting system and method. The system comprises a sensing layer, a decision-making layer and an execution layer. The sensing layer comprises an electroencephalogram acquisition and detection module and a visual identification and positioning module and is used for analyzing and identifying the intent of a user and identifying and locating positions of a corresponding cup and the user's mouth based on the user intent. The execution layer comprises a robotic arm control module that performs trajectory planning and control for a robotic arm based on an execution instruction received from a decision-making module. The decision-making layer comprises the decision-making module that is connected to the electroencephalogram acquisition and detection module, the visual identification and positioning module and the robotic arm control module to implement the acquisition and transmission of data of an electroencephalogram signal, a located position and a robotic arm status and the sending of the execution instruction for the robotic arm. The system combines the visual identification and positioning technology, a brain-computer interface and a robotic arm to facilitate paralyzed patients to drink water by themselves, improving the quality of life of the paralyzed patients.

A medical system includes: a slave having at least one moving part; an operation device having at least one operation part; and a processor that controls operations of the slave based on a conversion table that associates operations of the moving part of the slave with inputs of the operation part of the operation device. The processor is programmed to execute: acquiring user identification information of a user of the slave, slave identification information of the slave, and operation device identification information of the operation device, and generating and proposing the conversion table based on the user identification information, the slave identification information, and the operation device identification information.

A medical system includes: a slave having at least one moving part; an operation device having at least one operation part; and a processor that controls operations of the slave based on a conversion table that associates operations of the moving part of the slave with inputs of the operation part of the operation device. The processor is programmed to execute: acquiring user identification information of a user of the slave, slave identification information of the slave, and operation device identification information of the operation device, and generating and proposing the conversion table based on the user identification information, the slave identification information, and the operation device identification information.

A robotic assembly control system is disclosed. The robotic assembly control system includes an exoskeleton apparatus adapted to be worn by a user, at least one robotic assembly, the at least one robotic assembly controlled by the user by way of the exoskeleton, and at least one mobile platform, the at least one mobile platform controlled by the user and wherein the at least one robotic assembly is attached to the at least one mobile platform.

A robotic assembly control system is disclosed. The robotic assembly control system includes an exoskeleton apparatus adapted to be worn by a user, at least one robotic assembly, the at least one robotic assembly controlled by the user by way of the exoskeleton, and at least one mobile platform, the at least one mobile platform controlled by the user and wherein the at least one robotic assembly is attached to the at least one mobile platform.

A robotic surgical system has a user interface with a control arm that includes a passive axis system for maintaining degrees-of-freedom of a gimbal rotatably supported on the control arm as the gimbal is manipulated during a surgical procedure. The control arm includes a swivel member, a first member, and a second member. The swivel member is rotatable about a first axis. The first member rotatably coupled to the swivel member about a second axis that is orthogonal to the first axis. The second member rotatably coupled to the first member about a third axis that is parallel to the second axis. The gimbal rotatably supported by the second member about a fourth axis that is orthogonal to the third axis. The passive axis system correlating rotation of the swivel member about the first axis with rotation of the gimbal about the fourth axis.

A manipulation device 51 (master device) includes: an upper-body support part 65 which is mounted on an upper body of an operator P to be able to move together with the operator P as the operator P moves; and a movement command determination unit 94 which determines a movement control command value of a mobile body 1 (slave device) according to an observation value of a motion state including a movement speed of the upper-body support part 65 in a movement environment of the operator P. A reaction force received from the operator P by the upper-body support part 65 can be controlled by action control of a movement mechanism 52 of the manipulation device 51 and a lifting mechanism 60.

A manipulation device 51 (master device) includes: an upper-body support part 65 which is mounted on an upper body of an operator P to be able to move together with the operator P as the operator P moves; and a movement command determination unit 94 which determines a movement control command value of a mobile body 1 (slave device) according to an observation value of a motion state including a movement speed of the upper-body support part 65 in a movement environment of the operator P. A reaction force received from the operator P by the upper-body support part 65 can be controlled by action control of a movement mechanism 52 of the manipulation device 51 and a lifting mechanism 60.

A learning assistance system includes an operation control unit, a parameter acquisition unit, and a display control unit. The operation control unit causes an apparatus to be controlled to operate in accordance with force tactile sensation during operation by a user. The parameter acquisition unit acquires control parameters that are used for the control by the operation control unit. The operation control unit and the display control unit comparably provide, to a second user, a first control parameter acquired by the parameter acquisition unit in a case where the operation control unit controlled the operation of the apparatus based on operation by the first user and a second control parameter acquired by the parameter acquisition unit in a case where the operation control unit controlled the operation of the apparatus based on operation by the second user.