A robotic device includes a kinematic chain of a plurality of components, movable relative to each other; a sensor device configured to capture a force and/or moment exerted on at least one of the mobile components; a control device configured to control a movement of the at least one of the mobile components, in the direction of the force that is exerted, as a function of the force captured by the control device and/or of the moment captured by the control device; and a first capture device coupled to the control device and provided for the purpose of contactlessly capturing an operating action of an operator. In a normal operating mode, the control device is configured to specify a mobility of at least one of the mobile components as a function of the captured operating action, improving accuracy and reliability of the device in interaction with a human operator.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.

Embodiments relate to a computer-assisted robotic system, In some embodiments, the system includes a head input device, the head input device comprising a head input sensor configured to provide head input signals indicative of a an operator's head inputs, and a foot input device comprising a foot input sensor configured to provide foot input signals indicative of the operator's foot inputs. The system further includes a controller, configured to process the head input signals and the foot input signals, and identify, based on the processed head and foot input signals, that the operator has provided a combination of head and foot inputs corresponding to a steerable viewer mode activation command. The controller is further configured to cause the robotic system to enter a steerable viewer mode in response to identifying that the operator has provided a combination.