A grasping system includes a robotic arm having a gripper. A fixed sensor monitors a grasp area and an onboard sensor moves with the gripper also monitors the area. A controller receives information indicative of a position of an object to be grasped and operates the robotic arm to bring the gripper into a grasp position adjacent the object based on information provided by the fixed sensor. The controller is also programmed to operate the gripper to grasp the object in response to information provided by the first onboard sensor.

A method is provided that includes controlling a robotic gripping device to cause a plurality of digits of the robotic gripping device to move towards each other in an attempt to grasp an object. The method also includes receiving, from at least one non-contact sensor on the robotic gripping device, first sensor data indicative of a region between the plurality of digits of the robotic gripping device. The method further includes receiving, from the at least one non-contact sensor on the robotic gripping device, second sensor data indicative of the region between the plurality of digits of the robotic gripping device, where the second sensor data is based on a different sensing modality than the first sensor data. The method additionally includes determining, using an object-in-hand classifier that takes as input the first sensor data and the second sensor data, a result of the attempt to grasp the object.

A robotic gripping device is provided. The robotic gripping device includes a palm and a plurality of digits coupled to the palm. The robotic gripping device also includes a time-of-flight sensor arranged on the palm such that the time-of-flight sensor is configured to generate time-of-flight distance data in a direction between the plurality of digits. The robotic gripping device additionally includes an infrared camera, including an infrared illumination source, where the infrared camera is arranged on the palm such that the infrared camera is configured to generate grayscale image data in the direction between the plurality of digits.

Embodiments are generally directed to generating a training dataset of labelled examples of sensor images and grasp configurations using a set of three-dimensional (3D) models of objects, one or more analytic mechanical representations of either or both of grasp forces and grasp torques, and statistical sampling to model uncertainty in either or both sensing and control. Embodiments can also include using the training dataset to train a function approximator that takes as input a sensor image and returns data that is used to select grasp configurations for a robot grasping or targeting mechanism.

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 robotic gripping device is provided. The robotic gripping device includes a palm and a plurality of digits coupled to the palm. The robotic gripping device also includes a time-of-flight sensor arranged on the palm such that the time-of-flight sensor is configured to generate time-of-flight distance data in a direction between the plurality of digits. The robotic gripping device additionally includes an infrared camera, including an infrared illumination source, where the infrared camera is arranged on the palm such that the infrared camera is configured to generate grayscale image data in the direction between the plurality of digits.

Systems and methods for determining a pose of an object held by a flexible end effector of a robot are disclosed. A method of determining a pose of the object includes receiving tactile data from tactile sensors, receiving curvature data from curvature sensors, determining a plurality of segments of the flexible end effector from the curvature data, assigning a frame to each segment, determining a location of each point of contact between the object and the flexible end effector from the tactile data, calculating a set of relative transformations and determining a location of each point relative to one of the frames, generating continuous data from the determined location of each point, and providing the continuous data to a pose determination algorithm that uses the continuous data to determine the pose of the object.

A multimodal sensing architecture utilizes an array of single sensor or multi-sensor groups (superpixels) to facilitate advanced object-manipulation and recognition tasks performed by mechanical end effectors in robotic systems. The single-sensors/superpixels are spatially arrayed over contact surfaces of the end effector fingers and include, e.g., pressure sensors and vibration sensors that facilitate the simultaneous detection of both static and dynamic events occurring on the end effector, and optionally include proximity sensors and/or temperature sensors. A readout circuit receives the sensor data from the superpixels and transmits the sensor data onto a shared sensor data bus. An optional multimodal control generator receives and processes the sensor data and generates multimodal control signals that cause the robot system's control circuit to adjust control operations performed by the end effector or other portions of the robot mechanism and when the sensor data indicates non-standard operating conditions.

A robot system including a master device configured to receive a manipulating instruction from an operator and transmit the received manipulating instruction as a manipulating input signal, a plurality of slave robots configured to operate according to the manipulating input signal transmitted from the master device, a management control device configured to manage operations of the plurality of slave robots, respectively, and an output device configured to output information transmitted from the management control device. The management control device determines a priority of transmitting the manipulating input signal from the master device to the slave robot among the plurality of slave robots that are in a standby state of the manipulating input signal, and transmits information related to the determined priority to the output device. Thus, the operator is able to efficiently transmit the manipulating input signal to the plurality of slave robots through the master device.

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.