A center of gravity of a robot device is estimated without utilization of a force sensor or the like. An information processing device including a center-of-gravity estimation unit that calculates, on the basis of torque applied to one or more joints included in each of a plurality of leg portions, reaction force applied from a ground contact surface to each of the plurality of leg portions, and that estimates a center of gravity of a robot device including the plurality of leg portions on the basis of the calculated reaction force on the plurality of leg portions.

A method includes steps of: capturing an image of a container; recognizing at least one object in the container based on the image; determining at least one first coordinate set corresponding to the at least one object; determining at least one second coordinate set that corresponds to target one (s) of the at least one first coordinate set and that relates to a fixed picking device of a robotic arm; adjusting position(s) of unfixed picking device(s) of the robotic arm if necessary; controlling the robotic arm to pick up one (s) of the at least one object that correspond(s) to the at least one second coordinate set with the fixed picking device and/or at least one unfixed picking device.

A trajectory generation device which generates a trajectory of a robot includes: a trajectory exploration graph generation unit which is configured to generate a trajectory exploration graph composed of a plurality of nodes for generating the trajectory; an acceleration upper limit value acquisition unit which is configured to acquire a first acceleration upper limit value based on orientations and an acceleration direction of the robot at a current node; a velocity and acceleration setting unit which is configured to set a first velocity representing a velocity when moving from the current node to a next node adjacent to the current node based on the acquired first acceleration upper limit value, and an acceleration; and a node cost calculation unit which is configured to calculate a moving time by using the set first velocity and the acceleration as cost from the current node to the next node.

Apparatus, systems, methods, and articles of manufacture for automatic robot perception programming by imitation learning are disclosed. An example apparatus includes a percept mapper to identify a first percept and a second percept from data gathered from a demonstration of a task and an entropy encoder to calculate a first saliency of the first percept and a second saliency of the second percept. The example apparatus also includes a trajectory mapper to map a trajectory based on the first percept and the second percept, the first percept skewed based on the first saliency, the second percept skewed based on the second saliency. In addition, the example apparatus includes a probabilistic encoder to determine a plurality of variations of the trajectory and create a collection of trajectories including the trajectory and the variations of the trajectory. The example apparatus also includes an assemble network to imitate an action based on a first simulated signal from a first neural network of a first modality and a second simulated signal from a second neural network of a second modality, the action representative of a perceptual skill.

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.

A robot system includes a mobile robot configured to move, a portable teaching device including a display section configured to display information, the portable teaching device teaching the mobile robot, a first detecting section configured to detect a present position of the portable teaching device, a second detecting section configured to detect a present position of the mobile robot, and a display control section configured to cause, based on a detection result of the first detecting section and a detection result of the second detecting section, the display section to display the present position of the portable teaching device and the present position of the mobile robot.

A robot system includes a robot, a vision sensor, a target position generation circuit, an estimation circuit, and a control circuit. The robot includes an end effector and is configured to work via the end effector on a workpiece which is disposed at a relative position and which is relatively movable with respect to the end effector. The vision sensor is configured to take an image of the workpiece. The target position generation circuit is configured to, based on the image, generate a target position of the end effector at every generation interval. The estimation circuit is configured to, at least based on relative position information related to the relative position, estimate a change amount in the relative position at every estimation interval. The control circuit is configured to control the robot to move the end effector based on the target position and the change amount.

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.

A robot teaching device includes: a display device; an operation key formed of a hard key or a soft key and including an input changeover switch; a microphone; a voice recognition section; a correspondence storage section storing each of a plurality of types of commands and a recognition target word in association with each other; a recognition target word determination section configured to determine whether a phrase represented by character information includes the recognition target word; and a command execution signal output section configured to switch, in response to the input changeover switch being operated, between a first operation in which a signal for executing the command corresponding to an operation to the operation key is outputted and a second operation in which a signal for executing the command associated with the recognition target word represented by the character information is outputted.

A feedforward control method comprising steps of: acquiring kinematic parameters of each joint of a robot based on inverse kinematics according to a pre-planned robot motion trajectory, and setting a center of a body of the robot as a floating base; determining a six-dimensional acceleration of a center of mass of each joint of the robot in a base coordinate system using a forward kinematics algorithm, based on the kinematic parameters of each joint of the robot, and converting the six-dimensional acceleration of the center of mass of each joint of the robot in the base coordinate system to a six-dimensional acceleration in a world coordinate system; and calculating a torque required by a motor of each joint of the robot using an inverse dynamic algorithm, and controlling the motors of corresponding joints of the robot.