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1 / 16,003
1.WO/2026/102447REDUCING SENSITIVITY OF A FORCE/TORQUE SENSOR TO VARIATIONS IN BOUNDARY CONDITIONS
WO - 15.05.2026
Int.Class G01L 1/00
GPHYSICS
01MEASURING; TESTING
LMEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
1Measuring force or stress, in general
 Appl.No PCT/US2025/054973 Applicant ATI INDUSTRIAL AUTOMATION, INC. Inventor LIPSEY, Joseph
Both mathematical and mechanical methods improve observed accuracies when F/T sensors deployed are mounted to tools in the field. Due to differences in boundary conditions between manufacturer tooling and the field tooling when deployed, differences may arise in calibration matrices calculated at time of manufacture and those required for use in the field. Mathematical methods of correcting or creating new calibration matrices are disclosed. Additionally, one or two boundary condition normalizing plates present uniform forces and torques to deformable members, regardless of boundary conditions.
2.WO/2026/098412METHOD AND APPARATUS FOR SYNCHRONIZING AI ALGORITHM MODELS FOR HOUSEHOLD ROBOT, AND DEVICE AND STORAGE MEDIUM
WO - 15.05.2026
Int.Class B25J 9/16
BPERFORMING OPERATIONS; TRANSPORTING
25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; HANDLES FOR HAND IMPLEMENTS; WORKSHOP EQUIPMENT; MANIPULATORS
JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
9Programme-controlled manipulators
16Programme controls
 Appl.No PCT/CN2025/132231 Applicant E-SURFING DIGITAL LIFE TECHNOLOGY CO., LTD Inventor MA, Baoshan
Disclosed in the present invention are a method and apparatus for synchronizing AI algorithm models for a household robot, and a device and a storage medium, which are used for solving the problem of it being difficult to meet requirements for large-scale, efficient and automated upgrades due to the upgrade of AI algorithm models of existing household robots relying on manual operations and a centralized management policy. The method of the present invention comprises: acquiring position information of a household robot; receiving device information, an operating state and current home environment information which are sent by the household robot; on the basis of the position information, determining a device state of the household robot; on the basis of the device state, the device information, the operating state and the current home environment information, matching several target AI algorithm models from a preset AI algorithm library; and synchronizing the target AI algorithm models to the household robot.
3.WO/2026/100826INTELLIGENT EXPLORATION ROBOT AND INTELLIGENT CLOSED PIPELINE EXPLORATION SYSTEM INCLUDING SAME
WO - 15.05.2026
Int.Class F16L 55/32
FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
16ENGINEERING ELEMENTS OR UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
LPIPES; JOINTS OR FITTINGS FOR PIPES; SUPPORTS FOR PIPES, CABLES OR PROTECTIVE TUBING; MEANS FOR THERMAL INSULATION IN GENERAL
55Devices or appurtenances for use in, or in connection with, pipes or pipe systems
26Pigs or moles, i.e. devices movable in a pipe or conduit with or without self-contained propulsion means
28Constructional aspects
30of the propulsion means, e.g. towed by cables
32being self-contained
 Appl.No PCT/KR2024/096590 Applicant MORPHING I INC. Inventor KIM, Ki Young
An intelligent closed pipeline exploration system according to one embodiment of the present invention comprises: an intelligent exploration robot; and an input adjustment device provided to adjust the exploration distance of the intelligent exploration robot when the intelligent exploration robot explores a closed pipeline. The intelligent exploration robot includes: a camera module provided to acquire image data; an acoustic sensor provided to acquire acoustic data generated in the closed pipeline; an artificial intelligence module provided to perform artificial intelligence learning; and a control module electrically connected to the camera module, the acoustic sensor, and the artificial intelligence module. The control module can acquire image data inside the closed pipeline by using the camera module, acquire acoustic data generated in the closed pipeline by using the acoustic sensor, generate refined data by performing data refinement on the acquired image data and acoustic data through pre-processing, generate labeling data through data processing in which labeling is performed on the refined data on the basis of a class defined in advance for a problem area of the closed pipeline, generate training data for the problem area by performing artificial intelligence learning on the labeling data by using the artificial intelligence module, and perform identification and prediction regarding the problem area for newly acquired new image data and new acoustic data on the basis of the training data.
4.WO/2026/102272APPARATUS AND METHOD FOR AUTOMATIC PANEL CENTERING
WO - 15.05.2026
Int.Class H10P 72/50
Appl.No PCT/US2025/054588 Applicant BROOKS AUTOMATION US, LLC Inventor KRUPYSHEV, Alexander, G.
A right quadrilateral panel automatic centering system for automatic centering of a right quadrilateral panel for a semiconductor processing apparatus is provided and includes: a panel transport apparatus having an end effector with a holding station having a predetermined center, the end effector being configured to hold the right quadrilateral panel at the holding station; a sensor being configured to effect, substantially coincident, with the panel transport apparatus in motion, sensing of an edge of the right quadrilateral panel held on the end effector; and a controller that moves, with the panel transport apparatus, the right quadrilateral panel so the sensor senses the edge. The controller, from sensor data, characterizes respective lines of each of the intersecting edges so as to resolve an eccentricity of the right quadrilateral panel with the predetermined center and a rotation angle of the right quadrilateral panel relative to the predetermined reference frame.
5.WO/2026/100455CONTROL DEVICE AND PROGRAM
WO - 15.05.2026
Int.Class B23K 20/12
BPERFORMING OPERATIONS; TRANSPORTING
23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
KSOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
20Non-electric welding by applying impact or other pressure, with or without the application of heat, e.g. cladding or plating
12the heat being generated by friction; Friction welding
 Appl.No PCT/JP2025/038244 Applicant AISIN CORPORATION Inventor TOKUDA Yoshinori
The present invention appropriately controls an articulated robot for friction stir welding without capturing images of a weld line. Disclosed is a control device for an articulated robot that comprises a rotary tool that makes it possible to friction stir weld (FSW) two members to be welded. The control device comprises a first acquisition unit that acquires control instruction data for moving the rotating rotary tool along a target trajectory while the rotary tool is pressed into an intended welding site between the two members to be welded, a robot control unit that outputs command values based on the control instruction data to rotate the rotary tool and move the rotary tool along the target trajectory, and a second acquisition unit that acquires actual measurement data for the movement trajectory of the rotary tool when the rotary tool is actually working on the two members to be welded under control by the robot control unit. The robot control unit performs feedback control such that the difference between the actual measurement data and the target trajectory is 0.
6.WO/2026/101460MULTI MODAL ROBOT TRAINING USING CGI VIDEOS
WO - 15.05.2026
Int.Class B25J 9/16
BPERFORMING OPERATIONS; TRANSPORTING
25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; HANDLES FOR HAND IMPLEMENTS; WORKSHOP EQUIPMENT; MANIPULATORS
JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
9Programme-controlled manipulators
16Programme controls
 Appl.No PCT/SG2025/050715 Applicant EMAGE VISION PTE. LTD. Inventor WONG, Soon Wei
MULTI MODAL ROBOT TRAINING USING CGI VIDEOS An articulated Robot herein referred to as an automated system is typically deployed in industrial environments to perform critical tasks at high speed and accuracy. They require to be trained at many different tasks such as loading, unloading, gripping & releasing an object to name a few. Modern Robots have capabilities to learn by observing a human or another Robot perform the sequence of tasks and record the movements to formulate a control plan based on the tasks to be executed by the automated system henceforth referred to as a Robot, with the aid of a computer. However such methods are time consuming and prone to errors. The present invention discloses a solution that utilises a computer-generated imagery (CGI) video in combination with Computer aided design (CAD) process, to enable the generation of a control program for a Robot as contained in the CGI input. Further, machine learning, reinforced learning, Generative Artificial Intelligence and predictive analytics are incorporated within the control program, to help enhance the performance of the control program by fine tuning the operating models for efficient and quick deployment of Robots in different manufacturing environments. The control program may subsequently be used to evaluate the robot's performance and provide feedback for recalibrating the robot control program.
7.WO/2026/101024ELECTRONIC DEVICE AND CONTROL METHOD THEREFOR
WO - 15.05.2026
Int.Class B25J 13/06
BPERFORMING OPERATIONS; TRANSPORTING
25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; HANDLES FOR HAND IMPLEMENTS; WORKSHOP EQUIPMENT; MANIPULATORS
JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
13Controls for manipulators
06Control stands, e.g. consoles, switchboards
 Appl.No PCT/KR2025/015927 Applicant SAMSUNG ELECTRONICS CO., LTD. Inventor HAN, Segwon
Disclosed is an electronic device. One or more processors, when instructions are individually or collectively executed, cause the electronic device to: receive, from a server via a communication circuit, mapping information to which at least one item carried by each of a plurality of robots is mapped; when a user input for selecting one item among a plurality of items is received, identify at least one robot corresponding to the selected item among the plurality of robots on the basis of the mapping information; and transmit a signal for calling the identified robot to the identified robot via the communication circuit.
8.WO/2026/101129SURGICAL ROBOT SYSTEM
WO - 15.05.2026
Int.Class A61B 34/30
AHUMAN NECESSITIES
61MEDICAL OR VETERINARY SCIENCE; HYGIENE
BDIAGNOSIS; SURGERY; IDENTIFICATION
34Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
30Surgical robots
 Appl.No PCT/KR2025/017684 Applicant SUNGKWANG MEDICAL FOUNDATION Inventor KIM, Bowook
An embodiment of the present invention provides a surgical robot system comprising: a common port assembly including a first insertion path and a second insertion path that are spaced apart from each other; a first robot arm which supports and drives a first cannula guided along the first insertion path and a first surgical instrument arranged inside the first cannula; a second robot arm which supports and drives a second cannula guided along the second insertion path and a second surgical instrument arranged inside the second cannula; and a control unit which controls the first robot arm and the second robot arm, wherein the first surgical instrument is a flexible surgical instrument, and the second surgical instrument is a rigid surgical instrument.
9.WO/2026/098774METHOD AND DEVICE FOR DEMONSTRATION-BASED ROBOT PROGRAMMING SUPPLEMENTED BY SPOKEN INTERACTION
WO - 15.05.2026
Int.Class B25J 9/16
BPERFORMING OPERATIONS; TRANSPORTING
25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; HANDLES FOR HAND IMPLEMENTS; WORKSHOP EQUIPMENT; MANIPULATORS
JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
9Programme-controlled manipulators
16Programme controls
 Appl.No PCT/EP2024/081368 Applicant ABB SCHWEIZ AG Inventor TÄLLBERG, Kajsa
A method of programming an industrial robot (100), which comprises a robot manipulator (110) and a robot controller (120), comprising: recording movements of a robot manipulator during a demonstration-based programming session, to obtain a robot trajectory; capturing speech data while recording the movements of the robot manipulator; using a natural-language model, parsing the speech data into at least one robot parameter value and annotating the robot trajectory with the robot parameter value; and, on the basis of the annotated robot trajectory, generating a robot program. The method further comprises outputting spoken guidance to an operator (190) before or during the demonstration-based programming session, or between completion of the programming session and the generating of the robot program, or after an execution of the robot program by the industrial robot.
10.WO/2026/100765METHOD FOR SNN-BASED CONTROL OF ROBOTIC ARM IMITATING ARM MOTION BY USING EMG AND DVS
WO - 15.05.2026
Int.Class B25J 13/08
BPERFORMING OPERATIONS; TRANSPORTING
25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; HANDLES FOR HAND IMPLEMENTS; WORKSHOP EQUIPMENT; MANIPULATORS
JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
13Controls for manipulators
08by means of sensing devices, e.g. viewing or touching devices
 Appl.No PCT/KR2024/017509 Applicant KWANGWOON UNIVERSITY INDUSTRY-ACADEMIC COLLABORATION FOUNDATION Inventor PARK, Cheol Soo
A neuromorphic device for imitating and reproducing a person's hand or arm motion according to the present invention may comprise: a communication unit for receiving information on an electromyography (EMG) signal related to a motion of a person's hand or arm measured by an EMG sensor, and receiving information on a movement of the person's hand or arm detected by a dynamic vision sensor (DVS) camera; and a processor for converting the received information on the EMG signal into a spike signal, applying, to a predetermined trained spiking neural network (SNN) model, the converted spike signal and the information on the movement of the person's hand or arm received from the DVS camera, and outputting a class corresponding to the motion of the person's hand or arm among classes defined in advance on the basis of movement and position.
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