Technological development and optimization of pushing and grasping functions in robot arms: A review

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system’s performance when the number of agents increases. To this end, two different frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots, such as the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in experiences with real and virtual robots regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

/pdf/scalability-of-cyber-physical-systems-with-real-and-virtual-1lcw3i6l.pdf

Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2

We present TELESIM, a modular and plug-and-play framework for direct teleoperation of a robotic arm using a digital twin as the interface between the user and the robotic system. We tested TELESIM by performing a user survey with 37 participants on two different robots using two different control modalities: a virtual reality controller and a finger mapping hardware controller using different grasping systems. Users were asked to teleoperate the robot to pick and place 3 cubes in a tower and to repeat this task as many times as possible in 10 minutes, with only 5 minutes of training beforehand. Our experimental results show that most users were able to succeed by building at least a tower of 3 cubes regardless of the control modality or robot used, demonstrating the user-friendliness of TELESIM. 

https://export.arxiv.org/pdf/2309.10579v2.pdf

TELESIM: A Modular and Plug-and-Play Framework for Robotic Arm Teleoperation using a Digital Twin

Purpose: The increasing integration of intelligent devices and automation technologies in our daily lives has led to the development of smart homes, where various devices and systems are interconnected to provide enhanced comfort, convenience, and energy efficiency. Simulation tools are vital in designing, testing, and validating innovative home systems before their physical implementation. This research paper presents an intelligent home simulation framework implemented in CoppeliaSim. The simulation framework utilizes the C# programming language and leverages WebSocket communication to establish real-time interactions between the simulation environment and external applications. It discusses the architecture and implementation details of the simulation framework, highlighting the integration of CoppeliaSim, C#, and WebSocket. Design/Methodology/Approach: CoppeliaSim was chosen as the simulation platform due to its robust features, flexibility, and support for robotics and automation simulations. The simulation framework was developed using the C# programming language. C# provides a rich set of libraries and tools for efficient development, and its integration with CoppeliaSim allowed seamless communication and control of the simulated intelligent home environment. WebSocket communication established real-time interactions between the simulation environment and external applications. Findings/Result: The simulation framework successfully created a realistic, intelligent home environment, accurately representing various components and systems in typical smart homes. It effectively replicated real-world behaviors and interactions of intelligent home devices. The innovative home simulation framework highlighted its ability to accurately simulate an intelligent home environment, facilitate real-time interactions, and evaluate system performance. Originality/Value: The integration of CoppeliaSim, C#, and WebSocket communication in developing an intelligent home simulation framework presents a novel approach. While CoppeliaSim is a widely used simulation platform, combining C# and WebSocket communication provides an innovative and efficient way to create a brilliant home environment and enable real-time interactions with external applications. Paper Type: Simulation-based Research. 

Smart Home Simulation in CoppeliaSim Using C# Through WebSocket

For many years simulations are an important tool for researchers in many fields of application. With ongoing improvements in computing power and the rising requirements in the industry, simulation software has to shift the focus more towards industrial use cases. Especially in robotics and machine learning applications, the physical behavior has to be reproduced as realistic as possible to avoid unwanted collisions during runtime. In general, applications such as mounting or bin picking with an automated robot shall be evaluated. Therefore this paper investigates three in-use and one newly published software environment with included physics engine for realistic simulations that are commercially available. For comparison, a benchmark with collisions between two gears to imitate a mounting process is implemented and key features are defined. Only two of the simulation software manage to pass the benchmark. Despite that, both of them show restrictions revealing a lack of reliable software for realistic robot interaction simulation.

Comparison of Commercial Physics-Based Simulation Environments with a Collision-Rich Benchmark

Simulation software is a powerful tool for robotics research, allowing the virtual representation of the real world. However, with the rise of the Robot Operating System (ROS), there are new simulation software packages that have not been compared within the literature. This paper proposes a systematic review of simulation software compatible with ROS version 2. The focus is research in robotics arm manipulation as it represents the most often used robotic application in industry and their future applicability to digital twins. For this, we thus benchmark simulation software under similar parameters, tasks and scenarios and evaluate them in terms of their capability for long-term operations, success at completing a task, repeatability and resource usage. We find that there is no best simulation software overall. Still, two simulation packages (Ignition and Webots) have higher stability than others while, in terms of resource usage, PyBullet and Coppeliasim consume less than their competitors.

A Systematic Comparison of Simulation Software for Robotic Arm Manipulation using ROS2

pdf/can-real-to-sim-approaches-capture-dynamic-fabric-behavior-wipf32k00ayp.pdf

Can Real-to-Sim Approaches Capture Dynamic Fabric Behavior for Robotic Fabric Manipulation?

Surface defects are one of the largest contributors to low yield in the manufacturing sector. Accurate and reliable detection of defects during the manufacturing process is therefore of great value across the sector. State-of-the-art approaches to automated defect detection yield impressive performance on current datasets, yet still fall short in real-world manufacturing settings and developing improved methods relies on large datasets representative of real-world scenarios. Unfortunately, high-quality, high-precision RGB+3D industrial anomaly detection datasets are scarce, and typically do not reflect real-world industrial deployment scenarios. To address this, we introduce 3D-ADAM, the first large-scale industry-relevant dataset for high-precision 3D Anomaly Detection. 3D-ADAM comprises 14,120 high-resolution scans across 217 unique parts, captured using 4 industrial depth imaging sensors. It includes 27,346 annotated defect instances from 12 categories, covering the breadth of industrial surface defects. 3D-ADAM uniquely captures an additional 8,110 annotations of machine element features, spanning the range of relevant mechanical design form factors. Unlike existing datasets, 3D-ADAM is captured in a real industrial environment with variations in part position and orientation, camera positioning, ambient lighting conditions, as well as partial occlusions. Our evaluation of SOTA models across various RGB+3D anomaly detection tasks demonstrates the significant challenge this dataset presents to current approaches. We further validated the industrial relevance and quality of the dataset through an expert labelling survey conducted by industry partners. By providing this challenging benchmark, 3D-ADAM aims to accelerate the development of robust 3D Anomaly Detection models capable of meeting the demands of modern manufacturing environments.

pdf/3d-adam-a-dataset-for-3d-anomaly-detection-in-advanced-p50jillw3s84.pdf

3D-ADAM: A Dataset for 3D Anomaly Detection in Advanced Manufacturing

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Papers

A Systematic Comparison of Simulation Software for Robotic Arm Manipulation using ROS2

TELESIM: A Modular and Plug-and-Play Framework for Robotic Arm Teleoperation using a Digital Twin

Can Real-to-Sim Approaches Capture Dynamic Fabric Behavior for Robotic Fabric Manipulation?

3D-ADAM: A Dataset for 3D Anomaly Detection in Advanced Manufacturing