Patent classifications
G05B2219/40629
RUNTIME ASSESSMENT OF SUCTION GRASP FEASIBILITY
An autonomous system can detect out-of-distribution (OOD) data in robotic grasping systems, based on evaluating image inputs of the robotic grasping systems. Furthermore, the system makes various decisions based on detecting the OOD data, so as to avoid inefficient or hazardous situations or other negative consequences (e.g., damage to products). For example, the system can determine whether a suction-based gripper is optimal for grasping objects in a given scene, based at least in part on determining whether an image defines OOD data.
Methods and systems for distributing remote assistance to facilitate robotic object manipulation
Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.
Methods And Systems For Distributing Remote Assistance To Facilitate Robotic Object Manipulation
Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.
Movement path drawing device
A movement path drawing device includes an execution time storage unit that stores execution times of respective blocks of control programs, a program analysis unit that creates movement command data by analyzing the control programs, a movement path creation unit that creates the movement paths of the movable parts on the basis of the created movement command data, a drawing execution control unit that performs drawing execution control for drawing movement paths indicating a positional relationship between the movable parts of the plurality of systems of the machine at a predetermined time on the basis of the execution times of the respective blocks and the movement paths of the movable parts, created by the movement path creation unit, and a drawing unit that executes drawing processing for drawing the movable parts of the plurality of systems.
Visual perception and techniques for placing inventory into pods with a robotic workcell
Techniques and systems for performing a perception analysis for a robotic stowing operation are described. An example technique includes obtaining, via multiple sensors, multiple first images, wherein each first image is an image of a different container of an inventory holder within a robotic workcell. A first machine learning (ML) and image processing pipeline is performed with the first images to determine displacement locations for the containers of the inventory holder. A second ML and image processing pipeline is performed with the first images to determine content signatures for the containers. A plan is generated for stowing a first item into a first container, based at least in part on the plurality of content signatures and the plurality of displacement locations. A robotic apparatus is controlled to stow the first item into the first container, based on the plan.