A system comprises a database; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive at least one of sensory data from a robot and images from a camera, identify and build models of objects in an environment, wherein the model encompasses immutable properties of identified objects including mass and geometry, and wherein the geometry is assumed not to change, estimate the state including position, orientation, and velocity, of the identified objects, determine based on the state and model, potential configurations, or pre-grasp poses, for grasping the identified objects and return multiple grasping configurations per identified object, determine an object to be picked based on a quality metric, translate the pregrasp poses into behaviors that define motor forces and torques, communicate the motor forces and torques to the robot.

Provided are a control device, a control method, and a control program capable of realizing natural interaction between a human and a robot like between humans. A control device according to an embodiment includes a slip detection unit (15, 104) and a control unit (10). The slip detection unit detects a slip of a target object gripped by a grip portion. The control unit controls a gripping force with which the grip portion grips the target object based on the slip detected by the slip detection unit. The control unit estimates an external force applied to the target object gripped by the grip portion based on the slip detected by the slip detection unit, and controls the gripping force based on the estimated external force.

The present technology relates to an information processing device, an information processing method, a program, and a robot capable of estimate a value outside a detection range of a sensor. A control device of a first aspect of the present technology is a device that acquires detection results of a sensor unit composed of a plurality of sensors including a first sensor having a predetermined detection range, and a second sensor having a range in a detection range thereof in which detection by the first sensor is not possible and estimates a detected value of the first sensor outside the predetermined detection range on the basis of detection results of the second sensor. The present technology can be applied to a device that controls a robot having a hand part capable of gripping an object.

A system comprising: a database configured to store a multi-body model of a robot, the robot comprising a plurality of manipulators, and a plurality of joints and plurality of actuators and actuator motors configured to move the joints, and wherein the multi-body model includes a kinematic and geometric model of each manipulator, a catalog of models for objects to be manipulated, the models comprising a current configuration and a target configuration, and a functional mapping of sensory data to configurations of the robot and the manipulators needed to manipulate the objects; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive sensory data from within a constrained space, identify objects in the constrained space based on the received sensory data and the catalog of models, determine a target pose for the joints and the manipulators based on the sensory data and the current and target configurations associated with the identified object, and compute joint space positions to necessary to realize the target pose.

A system comprises a database; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive at least one of sensory data from a robot and images from a camera, identify and build models of objects in an environment, wherein the model encompasses immutable properties of identified objects including mass and geometry, and wherein the geometry is assumed not to change, estimate the state including position, orientation, and velocity, of the identified objects, determine based on the state and model, potential configurations, or pre-grasp poses, for grasping the identified objects and return multiple grasping configurations per identified object, determine an object to be picked based on a quality metric, translate the pre-grasp poses into behaviors that define motor forces and torques, communicate the motor forces and torques to the robot in order to allow the robot to perform a complex behavior generated from the behaviors.

A robotic gripper (end effector) for an arm-type robotic system includes a hierarchical sensor architecture that utilizes a central data processing circuit to generate rich sensory tactile data in response to pressure, temperature, vibration and/or proximity sensor data generated by finger-mounted sensor groups in response to interactions between the robotic gripper and a target object during robotic system operations. The rich sensory tactile data is used to generate feedback signals that directly control finger actuators and/or tactile information that is supplied to the robotic system's control circuit. Sensor data processing circuits are configured to receive single-sensor data signals in parallel from the sensor groups, and to transmit corresponding finger-level sensor data signal on a serial bus/signal line to the central data processing circuit. Each sensor group and an associated sensor data processing circuit are disposed on a PCB structure and mounted on a contact portion of an associated gripper finger.

A robot comprising: a chopstick, configured for at least four degrees of freedom of movement, a stiff body of shape and proportions approximate to a pool cue; an electromagnetic actuator, comprising a motor, for each degree of freedom of movement coupled with the stiff body, wherein the functional mapping from each actuator's motor current to torque output along an axis of motion is stored, and used in concert with a calibrated model of the robot for effective impedance control; and a 6-axis force/torque sensor mounted inline between the actuators and each chopstick.

Disclosed are various embodiments of a three-dimensional perception and object manipulation robot gripper configured for connection to and operation in conjunction with a robot arm. In some embodiments, the gripper comprises a palm, a plurality of motors or actuators operably connected to the palm, a mechanical manipulation system operably connected to the palm, a plurality of fingers operably connected to the motors or actuators and configured to manipulate one or more objects located within a workspace or target volume that can be accessed by the fingers. A depth camera system is also operably connected to the palm. One or more computing devices are operably connected to the depth camera and are configured and programmed to process images provided by the depth camera system to determine the location and orientation of the one or more objects within a workspace, and in accordance therewith, provide as outputs therefrom control signals or instructions configured to be employed by the motors or actuators to control movement and operation of the plurality of fingers so as to permit the fingers to manipulate the one or more objects located within the workspace or target volume. The gripper can also be configured to vary controllably at least one of a force, a torque, a stiffness, and a compliance applied by one or more of the plurality of fingers to the one or more objects.

According to one embodiment, a transporter includes a holder, a moving mechanism, a sensor, an operation controller, and a parameter estimator. The holder is configured to hold an object. The moving mechanism is configured to move the holder. The sensor is provided at the holder or the moving mechanism. The operation controller is configured to execute a test operation of moving the holder in a state in which the object is held by the holder. The parameter estimator is configured to estimate at least one parameter relating to the object based on a result of detection acquired by the sensor during the test operation.

A system comprising: a database configured to store a multi-body model of a robot, the robot comprising a plurality of manipulators, and a plurality of joints and plurality of actuators and actuator motors configured to move the joints, and wherein the multi-body model includes a kinematic and geometric model of each manipulator, a catalog of models for objects to be manipulated, the models comprising a current configuration and a target configuration, and a functional mapping of sensory data to configurations of the robot and the manipulators needed to manipulate the objects; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive sensory data from within a constrained space, identify objects in the constrained space based on the received sensory data and the catalog of models, determine a target pose for the joints and the manipulators based on the sensory data and the current and target configurations associated with the identified object, and compute joint space positions to necessary to realize the target pose.