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 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 sensor sheet includes unit sensor sheets configured to detect a physical property value at multiple points on a sensor layer, each unit sensor sheet including a first substrate, and an electrode layer and the sensor layer sequentially formed on one side of the first substrate; and a wiring substrate to which the unit sensor sheets are configured to be coupled, the wiring substrate including a second substrate, and a plurality of wirings provided on one side of the second substrate. One side of the wiring substrate and one side of each unit sensor sheet are facing each other. A conductive bonding member configured to electrically couple each unit sensor sheet and the wiring substrate with each other, is included between the electrode layer of each unit sensor sheet and at least one of the wirings of the wiring substrate.

A bag-shaped actuator system includes: a bag-shaped actuator including an airtight bag member and flowable particulates filled in the bag member; a bag-member communication pipe configured to communicate with an inside of the bag member; a low-air-pressure-source communication pipe configured to communicate with a low air pressure source; a high-air-pressure-source communication pipe configured to communicate with a high air pressure source; a switching mechanism configured to perform switching between communication destinations of the bag member such that the inside of the bag member communicates with any of external air, the low-air-pressure-source communication pipe, and the high-air-pressure-source communication pipe via the bag-member communication pipe; and a switching controlling portion configured to control the switching between the communication destinations by the switching mechanism.

A plurality of sensors are configured to provide respective outputs that reflect a sensed value associated with engagement of a robotic arm end effector with an item. The respective outputs of the plurality of sensors are used to make a determination associated with engagement of a robotic arm end effector with an item. A first value measured by a first sensor is used to determine a first input associated with a first factor. A second value measured by a second sensor is used to determine a second input associated with a second factor. The first input and the second input are provided to a multi-factor model configured to provide, based at least in part on the first input and the second input, an output associated with engagement of the robotic arm end effector with the item. The output of the multi-factor model is used to make the determination associated with engagement of the robotic arm end effector with the item.

A sensor system according to the present disclosure includes a substrate, a force sensor, a calculation unit, and an output part. The substrate includes a reference plane and an inclined surface. The force sensor is provided on the inclined surface and outputs signals in three-axis directions that correspond to an orthogonal axis direction that is orthogonal to the inclined surface and two-axis directions that are parallel to the reference plane. The calculation unit calculates a pressing force in each coordinate axis direction of rectangular coordinates formed of an axis vertical to the reference plane and two axes parallel to the reference plane and moments around the respective coordinate axes of the rectangular coordinates. The output part outputs calculation results.

There is provided a control device, a control method, and a program which are able to appropriately control a grip force of when a contact section and an object come into contact with each other. The control device includes a grip controller that controls a grip force related to a contact section depending on a contact force of when the contact section and an object come into contact with each other, the contact force being based on a sensing result obtained by a tactile sensor disposed at the contact section and a sensing result obtained by a force sensor disposed at the contact section.

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 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.

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.