Industrial Robotics

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Overview

Industrial robotics studies how robots can perform factory work such as assembly, machine tending, surface finishing, disassembly, and warehouse transport, often alongside people. Methods range from classical motion and force control, optimization, and safety monitoring to reinforcement learning, imitation learning, vision-language models, and digital twins. Benchmarks such as RoCo, WireCraft, LIBERO-Industry, and LABIT test collaboration, cable handling, production constraints, and long assembly sequences. A central challenge is turning capable demonstrations into reliable deployment despite changing parts and environments, contact uncertainty, tight cycle times, and strict safety requirements.

Latest papers

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67 papers7 papers in the last four weeks, up 17% on the four weeks before. 0.0% of all new papers.

Mar 2, 2026

From Transportation to Manipulation: Transforming Magnetic Levitation to Magnetic Robotics

Magnetic Levitation (MagLev) systems fundamentally increase the flexibility of in-machine material flow in industrial automation. Therefore, these systems enable dynamic throughput optimization, which is especially beneficial for high-mix low-volume manufacturing. Until now, MagLev installations have been used primarily for in-machine transport, while their potential for manipulation is largely unexplored. This paper introduces the 6D-Platform MagBot, a low-cost six degrees of freedom parallel kinematic that couples two movers into a composite robotic platform. Experiments show that the 6D-Platform MagBot achieves sub-millimeter positioning accuracy and supports fully autonomous pick up and drop off via a docking station, allowing rapid and repeatable reconfiguration of the machine. Relative to a single mover, the proposed platform substantially expands the reachable workspace, payload, and functional dexterity. By unifying transportation and manipulation, this work advances Magnetic Levitation towards Magnetic Robotics, enabling manufacturing solutions that are more agile, efficient, and adaptable.

Lara Bergmann, Noah Greis, Klaus Neumann

CITEC, Faculty of Technology, Bielefeld University, 33619 Bielefeld, Germany · Fraunhofer IOSB-INA, 32657 Lemgo, Germany

RoboticsRobotic ManipulationIndustrial Robotics
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Feb 19, 2026

Evolution of Safety Requirements in Industrial Robotics: Comparative Analysis of ISO 10218-1/2 (2011 vs. 2025) and Integration of ISO/TS 15066

Industrial robotics has established itself as an integral component of large-scale manufacturing enterprises. Simultaneously, collaborative robotics is gaining prominence, introducing novel paradigms of human-machine interaction. These advancements have necessitated a comprehensive revision of safety standards, specifically incorporating requirements for cybersecurity and protection against unauthorized access in networked robotic systems. This article presents a comparative analysis of the ISO 10218:2011 and ISO 10218:2025 standards, examining the evolution of their structure, terminology, technical requirements, and annexes. The analysis reveals significant expansions in functional safety and cybersecurity, the introduction of new classifications for robots and collaborative applications, and the normative integration of the technical specification ISO/TS 15066. Consequently, the new edition synthesizes mechanical, functional, and digital safety requirements, establishing a comprehensive framework for the design and operation of modern robotic systems.

Daniel Hartmann, Kristýna Hamříková, Aleš Vysocký +2

Robot SafetyIndustrial Robotics
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Feb 18, 2026

Smooth trajectory generation and hybrid B-splines-Quaternions based tool path interpolation for a 3T1R parallel kinematic milling robot

This paper presents a smooth trajectory generation method for a four-degree-of-freedom parallel kinematic milling robot. The proposed approach integrates B-spline and Quaternion interpolation techniques to manage decoupled position and orientation data points. The synchronization of orientation and arc-length-parameterized position data is achieved through the fitting of smooth piece-wise Bezier curves, which describe the non-linear relationship between path length and tool orientation, solved via sequential quadratic programming. By leveraging the convex hull properties of Bezier curves, the method ensures spatial and temporal separation constraints for multi-agent trajectory generation. Unit quaternions are employed for orientation interpolation, providing a robust and efficient representation that avoids gimbal lock and facilitates smooth, continuous rotation. Modifier polynomials are used for position interpolation. Temporal trajectories are optimized using minimum jerk, time-optimal piece-wise Bezier curves in two stages: task space followed by joint space, implemented on a low-cost microcontroller. Experimental results demonstrate that the proposed method offers enhanced accuracy, reduced velocity fluctuations, and computational efficiency compared to conventional interpolation methods.

Sina Akhbari, Mehran Mahboubkhah

Intelligent Automation Centre, Wolfson School of Mechanical, Electrical & Manufacturing Engineering, Loughborough University, Loughborough, UK · Department of Mechanical Engineering, University of Tabriz, 51666-16471, Tabriz, Iran

Trajectory GenerationRoboticsRobot Motion GenerationIndustrial RoboticsTrajectory Optimization
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Feb 18, 2026

Image Measurement Method for Automatic Insertion of Forks into Inclined Pallet

In order to insert a fork into a hole of a pallet by a forklift located in front of a pallet, it is necessary to control the height position, reach position, and tilt angle of the fork to match the position and orientation of the hole of the pallet. In order to make AGF (Autonomous Guided Forklift) do this automatically, we propose an image measurement method to measure the pitch inclination of the pallet in the camera coordinate system from an image obtained by using a wide-angle camera. In addition, we propose an image measurement method to easily acquire the calibration information between the camera coordinate system and the fork coordinate system necessary to apply the measurements in the camera coordinate system to the fork control. In the experiment space, a wide-angle camera was fixed at the backrest of a reach type forklift. The wide-angle images taken by placing a pallet in front of the camera were processed. As a result of evaluating the error by comparing the image measurement value with the hand measurement value when changing the pitch inclination angle of the pallet, the relative height of the pallet and the fork, and whether the pallet is loaded or not, it was confirmed that the error was within the allowable range for safely inserting the fork.

Nobuyuki Kita, Takuro Kato

TICO-AIST Cooperative Research Laboratory for Advanced Logistics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

Robotic InsertionIndustrial RoboticsObject Pose Estimation
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Feb 18, 2026

ICP-Based Pallet Tracking for Unloading on Inclined Surfaces by Autonomous Forklifts

This paper proposes a control method for autonomous forklifts to unload pallets on inclined surfaces, enabling the fork to be withdrawn without dragging the pallets. The proposed method applies the Iterative Closest Point (ICP) algorithm to point clouds measured from the upper region of the pallet and thereby tracks the relative position and attitude angle difference between the pallet and the fork during the unloading operation in real-time. According to the tracking result, the fork is aligned parallel to the target surface. After the fork is aligned, it is possible to complete the unloading process by withdrawing the fork along the tilt, preventing any dragging of the pallet. The effectiveness of the proposed method is verified through dynamic simulations and experiments using a real forklift that replicate unloading operations onto the inclined bed of a truck.

Takuro Kato, Mitsuharu Morisawa

T.Kato and M.Morisawa are with TICO-AIST Cooperative Research Laboratory for Advanced Logistics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.

Industrial RoboticsRobotic Manipulation
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Feb 17, 2026

VLM-DEWM: Dynamic External World Model for Verifiable and Resilient Vision-Language Planning in Manufacturing

Vision-language model (VLM) shows promise for high-level planning in smart manufacturing, yet their deployment in dynamic workcells faces two critical challenges: (1) stateless operation, they cannot persistently track out-of-view states, causing world-state drift; and (2) opaque reasoning, failures are difficult to diagnose, leading to costly blind retries. This paper presents VLM-DEWM, a cognitive architecture that decouples VLM reasoning from world-state management through a persistent, queryable Dynamic External World Model (DEWM). Each VLM decision is structured into an Externalizable Reasoning Trace (ERT), comprising action proposal, world belief, and causal assumption, which is validated against DEWM before execution. When failures occur, discrepancy analysis between predicted and observed states enables targeted recovery instead of global replanning. We evaluate VLM-DEWM on multi-station assembly, large-scale facility exploration, and real-robot recovery under induced failures. Compared to baseline memory-augmented VLM systems, VLM DEWM improves state-tracking accuracy from 56% to 93%, increases recovery success rate from below 5% to 95%, and significantly reduces computational overhead through structured memory. These results establish VLM-DEWM as a verifiable and resilient solution for long-horizon robotic operations in dynamic manufacturing environments.

Guoqin Tang, Qingxuan Jia, Gang Chen +4

School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China

VLMs for RoboticsMemory-Augmented VLMsEmbodied World ModelsIndustrial RoboticsRobot Failure Recovery
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Nov 13, 2025

Improving dependability in robotized bolting operations

Bolting operations are critical in industrial assembly and in the maintenance of scientific facilities, requiring high precision and robustness to faults. Although robotic solutions have the potential to improve operational safety and effectiveness, current systems still lack reliable autonomy and fault management capabilities. To address this gap, we propose a control framework for dependable robotized bolting tasks and instantiate it on a specific robotic system. The system features a control architecture ensuring accurate driving torque control and active compliance throughout the entire operation, enabling safe interaction even under fault conditions. By designing a multimodal human-robot interface (HRI) providing real-time visualization of relevant system information and supporting seamless transitions between automatic and manual control, we improve operator situation awareness and fault detection capabilities. A high-level supervisor (SV) coordinates the execution and manages transitions between control modes, ensuring consistency with the supervisory control (SVC) paradigm, while preserving the human operator's authority. The system is validated in a representative bolting operation involving pipe flange joining, under several fault conditions. The results demonstrate improved fault detection capabilities, enhanced operator situational awareness, and accurate and compliant execution of the bolting operation.

Lorenzo Pagliara, Vincenzo Petrone, Violeta Redondo +3

Department of Information Engineering, Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, Italy · GTD Science, Infrastructures & Robotics, Av. Leonardo Da Vinci, 2, Madrid, 28906, Spain · Universidad Politécnica de Madrid, Centre for Automation and Robotics (CAR) UPM-CSIC, José Gutiérrez Abascal, 2, Madrid, 28006, Spain

Industrial RoboticsRobotic AssemblyFault-Tolerant ControlRobot Failure DetectionHuman-Robot Collaboration
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