The present disclosure relates to a control device, a control method, and a program capable of supporting an object with a more appropriate supporting force. The control device includes a supporting force control unit that controls a supporting force for supporting an object on the basis of information regarding a shape of a contact portion in contact with the object and information regarding a shear force of the contact portion. The information regarding the shear force includes, for example, information regarding a shear displacement of the contact portion. The present disclosure can be applied to, for example, a control device, a control method, an electronic device, a robot, a support system, a gripping system, a program, and the like.

A tool control system may include: a tactile sensor configured to, when a tool holds a target object and slides the target object downward across the tool, obtain tactile sensing data from the tool; one or more memories configured to store a target velocity and computer-readable instructions; and one or more processors configured execute the computer-readable instructions to: receive the tactile sensing data from the tactile sensor; estimate a velocity of the target object based on the tactile sensing data, by using one or more neural networks that are trained based on a training image of an sample object captured while the sample object is sliding down; and generate a control parameter of the tool based on the estimated velocity and the target velocity.

A robotic device includes an end effector device, a first sensor, and a controller. The end effector device includes two fingers for gripping a workpiece. The first sensor detects a pressure distribution on a gripping position on the workpiece by the two fingers. The controller performs, based on a temporal variation in the pressure distribution when the workpiece is lifted, posture control including rotation of the end effector device.

A plurality of sensors are configured to provide a corresponding output that reflects a sensed value associated with engagement of a robotic arm end effector with an item. The respective outputs of one or more sensors comprising the plurality of sensors are used to determine one or more inputs to a multi-modal model configured to provide, based at least in part on the one or more inputs, an output associated with slippage of the item within or from a grasp of the robotic arm end effector. A determination associated with slippage of the item within or from the grasp of the robotic arm end effector is made based at least in part on an output of the multi-modal model. A responsive action is taken based at least in part on the determination associated with slippage of the item within or from the grasp of the robotic arm end effector.

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.

A robot hand according to an embodiment of the present technology includes a finger unit and a guide member. The finger unit is capable of holding a flexible linear member such that the linear member is slidable in a longitudinal direction of the linear member, the linear member being a linear member whose one end is fixed. The guide member is mounted on the finger unit, and includes a guide section that guides the linear member to a predetermined position.

A control apparatus includes a robot having an arm, a driver, an end effector, a first detector, and a second detector, and a control device. The control device acts as a third detector, a calculator, and a controller. The third detector detects a slip direction of the object held by the end effector. The calculator calculates an angle defined by the slip direction detected by the third detector and a direction opposite to gravity. The controller causes the end effector holding the object to pivot by the angle calculated by the calculator, to align the slip direction detected by the third detector with the direction opposite to gravity.

A tool control system may include: a tactile sensor configured to, when a tool holds a target object and slides the target object downward across the tool, obtain tactile sensing data from the tool; one or more memories configured to store a target velocity and computer-readable instructions; and one or more processors configured execute the computer-readable instructions to: receive the tactile sensing data from the tactile sensor; estimate a velocity of the target object based on the tactile sensing data, by using one or more neural networks that are trained based on a training image of an sample object captured while the sample object is sliding down; and generate a control parameter of the tool based on the estimated velocity and the target velocity.

A plurality of sensors are configured to provide a corresponding output that reflects a sensed value associated with engagement of a robotic arm end effector with an item. The respective outputs of one or more sensors comprising the plurality of sensors are used to determine one or more inputs to a multi-modal model configured to provide, based at least in part on the one or more inputs, an output associated with slippage of the item within or from a grasp of the robotic arm end effector. A determination associated with slippage of the item within or from the grasp of the robotic arm end effector is made based at least in part on an output of the multi-modal model. A responsive action is taken based at least in part on the determination associated with slippage of the item within or from the grasp of the robotic arm end effector.

A robotic device includes an end effector device, a first sensor, and a controller. The end effector device includes two fingers for gripping a workpiece. The first sensor detects a pressure distribution on a gripping position on the workpiece by the two fingers. The controller performs, based on a temporal variation in the pressure distribution when the workpiece is lifted, posture control including rotation of the end effector device.