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.

The present invention makes an instruction for causing a transport robot to carry out transport easier for a person to understand. A transport system (1) is such that an address indicating a transport destination or a transport source is represented by a tree structure including a node indicating loading locations and a node indicating equipment to which the loading locations are provided, and when the address of the transport destination indicates equipment, a transport robot (20) sequentially loads objects to be transported in accordance with a preset loading priority order in loading locations where no objects to be transported have been loaded, from among the loading locations belonging to that equipment.

A conveyance robot system according to the present disclosure includes an intrusion detection sensor that detects an intrusion of an object into the arm opening, and a distance sensor that measures a clearance distance indicating a distance between an arm entry/exit surface and a shelf, the arm entry/exit surface being a surface of the conveyance robot in which the arm opening is provided from among surfaces of the conveyance robot 1 constituting the safety cover, and the object being stored in the shelf. The distance sensor is disposed at a fixed height of the shelf in a horizontal direction and at a height of the shelf corresponding to a part to be measured.

A learning dataset generation device includes: a memory that stores three-dimensional CAD data of a workpiece and a container; and one or more processors including hardware, wherein the one or more processors are configured to use the three-dimensional CAD data of the workpiece and the container, stored in the memory, to generate, in a three-dimensional virtual space, a plurality of imaging objects in which a plurality of the workpieces are bulk-loaded in different forms inside the container, acquire a plurality of virtual distance images by measuring each of the generated imaging objects by means of a virtual three-dimensional measurement machine disposed in the three-dimensional virtual space, accept at least one teaching position for each of the acquired virtual distance images, and generate a learning dataset by associating the accepted teaching position with each of the virtual distance images.

A robotic kitting machine is disclosed. In various embodiments, a robotic arm is used to move an item to a location in proximity to a slot into which the item is to be inserted. Force information generated by a force sensor is received via a communication interface. The force sensor information is used to align a structure comprising the item with a corresponding cavity comprising the slot, and the item is inserted into the slot.

A picking system is configured to pick items from, and put items into, storage containers. The picking system includes a picking station. The picking station includes: a picking system controller configured to receive product orders from a warehouse management system; at least one container contents handling position; a camera configured to produce an image of contents of a storage container; an image processing system in communication with the camera for processing the image produced by the camera in order to identify a position of a specific item in the storage container, and a robotic picking device. The image processing system is further in communication with a picking system controller and is adapted to inform the picking system controller of the position of the specific item. The robotic picking device is in communication with the picking system controller and is configured to, under guidance from the picking system controller, to pick said specific item from said position in the storage container. The camera and the robotic picking device are arranged to operate, at any one instance, on different containers such that the camera is producing an image and the image processing system is processing the produced image of the contents of a storage container in a first product order while the robotic picking device is handling a second storage container on the basis of an earlier image that has been produced by the camera and processed by the image processing system.

This document describes systems and methods for enhancing the efficiencies of order fulfillment and inventory management processes. For example, this document describes automated robotic systems that can autonomously pick and place a particular quantity of desired items from a container that is storing the items. The autonomous robotic systems can thereby facilitate order fulfillment and inventory management processes in an efficient manner. In particular, the systems and methods described herein can greatly reduce the amount of time required for a human worker to pick orders. Accordingly, the efficiency of item picking processes, as measured by the number of line items picked per human labor hour for example, is greatly enhanced.

Embodiments of the present disclosure are directed towards robotic systems and methods. The robot may include an end effector, a tool flange of the robot, and a joint. The end effector may include a contacting part configured to contact a workpiece. The joint may be positioned between, and connected to, the tool flange and the end effector. The joint may include a variable angle between the tool flange and the end effector.

A robotic system is disclosed. The system includes a communication interface that receives, from a sensor(s) deployed in a workspace, sensor data indicative of a current state of the workspace, the workspace comprising a pallet or other receptacle and a plurality of items stacked on or in the receptacle. The system includes one or more processors that control a robotic arm to place a first set of items on or in, or remove the first set of items from, the pallet or other receptacle, update a geometric model based on the first set of items placed on or in a receptacle, use the geometric model in combination with the sensor data to estimate a stack of one or more items on or in the receptacle, and use the estimated state to generate or update a plan to control the robotic arm to place a second set of items.

A robotic system is disclosed. The system includes a memory that stores for each of a plurality of items a set of attribute values. The system includes a processor(s) that uses the attribute values to simulate the placement of items, including by determining, iteratively, for each next item a placement location at which to place the item on a simulated stack of items on the pallet, using the attribute values and a geometric model of where items have been simulated to have been placed to estimate a state of the stack after each of a subset of simulated placements, and using the estimated state to inform a next placement decision. The steps of determining for each next item a placement location and estimating the state of the stack until all of at least a subset of the plurality of items have been simulated as having been placed on the stack.