Provided is a robot including a microphone configured to acquire a sound signal corresponding to a sound generated near the robot, a camera, an output interface including at least one of a display configured to output a wake-up screen or a speaker configured to output a wake-up sound when the robot wakes up, and a processor configured to recognize whether the acquired sound includes a voice of a person, activate the camera when the sound includes a voice of a person, recognize whether a person is present in an image acquired by the activated camera, set a wake-up word recognition sensitivity based on a recognition result as to whether a person is present, and recognize whether a wake-up word is included voice data of a user acquired through the microphone based on the set wake-up word recognition sensitivity.

Systems and methods for determining a location of a robot are provided. A method includes receiving, by a processor, a signal from a deformable sensor including data with respect to a deformation region in a deformable membrane of the deformable sensor resulting from contact with a first object. The data associated with contact with the first object is compared, by the processor, to details associated with contact with the first object to information associated with a plurality of objects stored in a database. The first object is identified, by the processor, as a first identified object of the plurality of objects stored in the database. The first identified object is an object of the plurality of objects stored in the database that is most similar to the first object. The location of the robot is determined, by the processor, based on a location of the first identified object.

Embodiments of the present disclosure provide methods for managing a robot system. In one method, orientations for links in the robot system may be obtained when the links are arranged in at least one posture, here each of the orientations indicates a direction pointed by one of the links. At least one image of an object placed in the robot system may be obtained from a vision device equipped on one of the links. Based on the orientations and the at least one image, a first mapping may be determined between a vision coordinate system of the vision device and a link coordination system of the link. Further, embodiments of present disclosure provide apparatuses, systems, and computer readable media for managing a robot system. The vision device may be calibrated by the first mapping and may be used to manage operations of the robot system.

A method for reducing vibration of a robot arm includes: a step of mounting at least one inertia actuator and at least one vibration signal capturing unit to a processing end of a robot arm; a step of applying the at least one vibration signal capturing unit to detect a vibration generated at the processing end of the robot arm so as to generate a vibration signal; a step of applying a central processing unit to evaluate the vibration signal and coordinates of the processing end of the robot arm so as to capture at least one set of corresponding control parameters for calculating at least one output force; and, a step of having the inertia actuator to apply the output force to the processing end of the robot arm for counteracting the vibration at the processing end of the robot arm.

A robot control device for a robot comprises a case and a connector board which is coupled to the case and includes a plurality of connectors which are disposed in a first region and a second region adjacent laterally to the first region. The plurality of the connectors may comprise a power connector which is disposed at a bottom of one of the first region or the second region and is coupled with a power supplier; and a processor connector which is disposed in a region different from that of the power supplier and is coupled with a processor.

A system and method for improving a position accuracy of a mobile robot is disclosed. A retroreflective device is mounted to the mobile robot and used by an absolute positioning device to use a laser beam to track a position of the mobile robot. The mobile robot receives position measurements. Various optimizations may be performed to support operating the mobile robot over a 360 degree range of azimuthal headings.

Disclosed is a deep reinforcement learning apparatus and method for a pick-and-place system. According to the present disclosure, a simulation learning framework is configured to apply reinforcement learning to make pick-and-place decisions using a robot operating system (ROS) in a real-time environment, thereby generating stable path motion that meets various hardware and real-time constraints.

Embodiments of architecture, systems, and methods to develop a learning/evolving system to robotically perform and model one or more activities of a medical procedure where the medical procedure may include diagnosing a patient's medical condition(s), treating medical condition(s), and robotically diagnosing a patient's medical condition(s) and performing one or more medical procedure activities based on the diagnosis without User intervention where the activities may be performed in computer-based environment formed by the learning/evolving system, live, or a combination thereof.

The foodstuff assembly system can include: a robot arm, a frame, a set of foodstuff bins, a sensor suite, a set of food utensils, and a computing system. The system can optionally include: a container management system, a human machine interface (HMI). However, the foodstuff assembly system 100 can additionally or alternatively include any other suitable set of components. The system functions to enable picking of foodstuff from a set of foodstuff bins and placement into a container (such as a bowl, tray, or other foodstuff receptacle). Additionally or alternatively, the system can function to facilitate transferal of bulk material (e.g., bulk foodstuff) into containers, such as containers moving along a conveyor line.

A component installation system includes an engagement clamp having a circular shape coupled to a robotic arm, being configured to engage an annular component. The component installation system further includes an actuator coupled to the engagement clamp and operable to cause the engagement clamp to engage and disengage the annular component, and a heating element coupled to the engagement clamp and arranged to heat the annular component engaged within the engagement clamp. The component installation system further includes a controller in communication with the robotic arm, the actuator and the heating element.