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Balancing Cobot Productivity and Longevity Through Pre-Runtime Developer Feedback

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第2期10卷 1617-1624页

作者： Kolvig-Raun, Emil Stubbe Hviid, Jakob Kjaergaard, Mikkel Baun Brorsen, Ralph Jacob, Peter Univ Southern Denmark SDU Software Engn DK-5230 Odense Denmark Universal Robots DK-5260 Odense Denmark

In our experience, the task of optimizing robot longevity and efficiency is challenging due to the limited understanding and awareness developers' have about how their code influences a robot's expected lifespan. Unfortunately, acquiring the necessary information for computations is a complex task, and the data needed for these calculations remains unattainable until after runtime. In software engineering, traditional Static Code Analysis (SCA) techniques are applied to address such challenges. Although effective in identifying software anomalies and inefficiencies without execution, current SCA techniques do not adequately address the unique requirements of Cyber-Physical Systems (CPSs) in robotics. In this study, we propose a novel Machine Learning (ML) approach to assess robot program lines, considering the balance between speed and lifespan. Our solution, trained on data from 1325 operational collaborative robots (cobots) from the Universal Robots (UR) e-Series, classifies program lines concerning the expected lifespan of the robot, considering program line arguments, expected resource usage, and asserted joint stress. The model achieves a worst-case accuracy of 90.43% through 10-fold cross-validation with a 50% data split. We also present a selection of programming lines illustrating various robot program cases and an example of longevity improvement. Finally, we publish a dataset containing 56405 unique program line executions, aiming to enhance the sustainability and efficiency of robotic systems and support future research.

关键词： Robots Software Data models Hardware Stress Runtime Codes Degradation Collaborative robots Kinematics AI-based methods data sets for robot learning software middleware and programming environments

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Computational Resources of Miniature Robots: Classification and Implications

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IEEE ROBOTICS AND AUTOMATION LETTERS 2019年第3期4卷 2722-2729页

作者： Trenkwalder, Stefan M. Univ Sheffield Dept Automat Control & Syst Engn Sheffield S10 2TN S Yorkshire England

When it comes to describing robots, many roboticists choose to focus on the size, types of actuators, or other physical capabilities. As most areas of robotics deploy robots with large memory and processing power, the question "how computational resources limit what a robot can do" is often overlooked. However, the capabilities of many miniature robots are limited by significantly less memory and processing power. At present, there is no systematic approach to comparing and quantifying the computational resources as a whole and their implications. This letter proposes computational indices that systematically quantify computational resources-individually and as a whole. Then, by comparing 31 state-of-the-art miniature robots, a computational classification ranging from non-computing to minimally-constrained robots is introduced. Finally, the implications of computational constraints on robotic software are discussed.

关键词： Performance evaluation and benchmarking software middleware and programming environments control architectures and programming swarms

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A Regret-Informed Evolutionary Approach for Generating Adversarial Scenarios for Black-Box Off-Road Autonomy Systems

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第6期9卷 5354-5361页

作者： Sender, Ted Brudnak, Mark Steiger, Reid Vasudevan, Ram Epureanu, Bogdan Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA US Army Combat Capabil Dev Command Ground Vehicle Syst Ctr Warren MI 48397 USA Ford Motor Co Dearborn MI 48126 USA

Developing autonomous vehicles (AVs) that operate in diverse and demanding environments is a difficult challenge. Two fundamental tools that can accelerate this process are testing an AV in diverse simulated environments and identifying core system weaknesses. While most efforts focus on improving these tools for on-road AVs, this letter focuses on an analogous set of tools for off-road AVs. A method called Black-Box Adversarially Compounding Regret Through Evolution (BACRE) is proposed for identifying adversarial scenarios using an evolutionary algorithm guided by a novel regret-based metric for general navigation tasks. A black-box approach is often preferable when system complexity can be diverse, like with off-road AVs, and when whole-system testing is required. A custom simulation platform is also provided to assist with the automated testing of AVs in diverse, unstructured environments. Numerical experiments demonstrate that BACRE's evolutionary process gradually increases scenario complexity to degrade vehicle performance (an effective and explainable process that comparable methods cannot achieve). Consequently, BACRE can streamline AV development by finding weaknesses at any development stage.

关键词： Planning under uncertainty simulation and animation software middleware and programming environments

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Design, Execution, and Postmortem Analysis of Prolonged Autonomous Robot Operations

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IEEE ROBOTICS AND AUTOMATION LETTERS 2018年第2期3卷 1056-1063页

作者： Brunner, Sebastian G. Lehner, Peter Schuster, Martin J. Riedel, Sebastian Belder, Rico Leidner, Daniel Wedler, Armin Beetz, Michael Stulp, Freek German Aerosp Ctr DLR RMC D-82234 Wessling Germany Univ Bremen IAI D-85748 Bremen Germany

In the context of space missions and terrestrial applications, both mission goals and task implementations for autonomous robots are becoming increasingly complex. Thus, the challenge of monitoring the achievement of task objectives and checking the correctness of their implementation is becoming more and more difficult. To tackle these problems, we propose an unified architecture that supports different stakeholders during the different phases of the deployment: 1) the design phase;2) the runtime phase;and 3) the postmortem analysis phase. Furthermore, we implement this architecture by enhancing our task programming framework RMC advanced flow control with powerful logging, debugging, and profiling capabilities. We demonstrate the efficiency of our approach in the context of the ROBEX mission, during which the DLR Lightweight Rover Unit autonomously deployed several seismometers in an unknown rough terrain on Mt. Etna, Sicily. The analysis results for a state machine consisting of more than 1500 states and more than 1900 transitions are presented. Finally, we give a comparison between our framework and related software tools.

关键词： Software middleware and programming environments field robots space robotics and automation autonomous agents mobile manipulation

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Try to Start It! The Challenge of Reusing Code in Robotics Research

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IEEE ROBOTICS AND AUTOMATION LETTERS 2019年第1期4卷 49-56页

作者： Cervera, Enric Jaume I Univ Robot Intelligence Lab Castellon de La Plana 12071 Spain

This letter reviews the source code published with the papers of a flagship robotics research conference, 2017 International Conference on Robotics and Automation. The aim is to investigate whether the code is actually useful, i.e., can he reused by an interested reader without much effort. The interest is twofold: for one side, it makes possible to replicate and validate the results of the research;for another side, it facilitates new progress on the field, since researchers can build new systems on top of existing work. Unfortunately, reusing code is not as straightforward as it could seem, and there is a need for tools that alleviate the effort for integrating someone else's code into the own user's system. We propose the use of Docker, a Linux container technology, to turn the source code repositories into executable images, that can be run and tested locally, in an isolated environment, without the need of a costly integration with the host system.

关键词： Software middleware and programming environments

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Autonomous Parallelization of Resource-Aware Robotic Task Nodes

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IEEE ROBOTICS AND AUTOMATION LETTERS 2019年第3期4卷 2599-2606页

作者： Brunner, Sebastian Georg Doemel, Andreas Lehner, Peter Beetz, Michael Stulp, Freek German Aerosp Ctr DLR Robot & Mechatron Ctr D-82234 Wessling Germany Univ Bremen Dept Comp Sci D-85748 Bremen Germany Univ Bremen Ctr Comp Technol D-85748 Bremen Germany

Robot task programming often leads to inefficient plans, as opportunities for parallelization and precomputation are usually not exploited by the programmer. This inefficiency is often especially obvious in mobile manipulation, where path planning and pose estimation algorithms are time-consuming operations. In this letter, we introduce the concept of' resource-aware task nodes (RATNs), a powerful descriptive action model for robots. Next, we propose an algorithm that executes so-called concurrent dataflow task networks (CDTNs), robot plans consisting of RATNs. It optimizes programmed plans based on two sources of information: 1) The control flow represented in the original task plan, whose constraints are relaxed to generate opportunities for parallelization and precomputation. 2) Dependencies between actions pertaining to resources, data flows, and world model changes, the latter being equivalent to preconditions and effects. CDTNshave been integrated in our open-source task programming framework RAFCON, and we show that it leads to 11%-29% improvement in terms of execution time in two simulated mobile manipulation scenarios.

关键词： Software middleware and programming environments autonomous agents mobile manipulation

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Ev-Conv: Fast CNN Inference on Event Camera Inputs for High-Speed Robot Perception

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IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第6期8卷 3174-3181页

作者： Durvasula, Sankeerth Guan, Yushi Vijaykumar, Nandita Univ Toronto Toronto ON M5R 0A3 Canada

Event cameras capture visual information with a high temporal resolution and a wide dynamic range. This enables capturing visual information at fine time granularities (e.g., microseconds) in rapidly changing environments. This makes event cameras highly useful for high-speed robotics tasks involving rapid motion, such as high-speed perception, object tracking, and control. However, convolutional neural network inference on event camera streams cannot currently perform real-time inference at the high speeds at which event cameras operate-current CNN inference times are typically closer in order of magnitude to the frame rates of regular frame-based cameras. Real-time inference at event camera rates is necessary to fully leverage the high frequency and high temporal resolution that event cameras offer. This letter presents Ev-Conv, a new approach to enable fast inference on CNNs for inputs from event cameras. We observe that consecutive inputs to the CNN from an event camera have only small differences between them. Thus, we propose to perform inference on the difference between consecutive input tensors, or the increment. This enables a significant reduction in the number of floating-point operations required (and thus the inference latency) because increments are very sparse. We design Ev-Conv to leverage the irregular sparsity in increments from event cameras and to retain the sparsity of these increments across all layers of the network. We demonstrate a reduction in the number of floating operations required in the forward pass by up to 98%. We also demonstrate a speedup of up to 1.6xfor inference using CNNs for tasks such as depth estimation, object recognition, and optical flow estimation, with almost no loss in accuracy.

关键词： Software architecture for robotic and automation computer architecture for robotic and automation software middleware and programming environments

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Map-Reduce-Style Job Offloading Using Historical Manufacturing Behavior for Edge Devices in Smart Factory

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IEEE ROBOTICS AND AUTOMATION LETTERS 2018年第4期3卷 2918-2925页

作者： Chen, Chao-Chun Su, Wei-Tsung Hung, Min-Hsiung Lin, Zhong-Hui Natl Cheng Kung Univ Inst Mfg Informat & Syst Tainan 701 Taiwan Aletheia Univ Dept Comp Sci & Informat Engn New Taipei 251 Taiwan Chinese Culture Univ Dept Comp Sci & Informat Engn Taipei 11114 Taiwan IBM Corp Dublin OH 43016 USA

For smart factories in the Industry 4.0 era, edge devices can be used to run intelligent software packages (i.e., manufacturing services) to support manufacturing activities of production equipment. However, this kind of edge device may fail to provide designed functionalities in time when it encounters a sudden high-computation (SHC) job that cannot be executed by the edge device itself within a required time constraint. Thus, how to assure that an edge device can effectively execute SHC jobs so as to provide manufacturing services to equipment in time is an important and challenging issue for smart manufacturing. Exiting job-shop scheduling (JSS) methods may optimally allocate jobs for production lines but cannot directly be applied to handle the edge devices SHC jobs, which occur irregularly and are hard to specify processing time slots for JSS methods. Aimed at resolving the above-mentioned issue, this letter proposes a novel manufacturing behavior-based map-reduce-style job offloading scheme. First, a distributed job processing architecture is designed to allow distributed edge devices to collaboratively complete an SHC job to support manufacturing. Next, a map-reduce-style program structure is developed so that an SHC job can be easily divided into multiple parts that can be executed in parallel by the selected edge devices, each device processing a part. Then, a mechanism of selecting proper edge devices to complete the SHC job, considering historical manufacturing behaviors of each edge device, is proposed for achieving high offloading efficiency. Finally, we simulate a factory with 20 machines to conduct integrated tests. Testing results demonstrate the effectiveness and excellent performance of the proposed scheme.

关键词： Intelligent and flexible manufacturing software middleware and programming environments smart factory automation job offloading edge computing

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Introducing Geometric Constraint Expressions Into Robot Constrained Motion Specification and Control

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IEEE ROBOTICS AND AUTOMATION LETTERS 2016年第2期1卷 1140-1147页

作者： Borghesan, Gianni Scioni, Enea Kheddar, Abderrahmane Bruyninckx, Herman Univ Leuven Dept Mech Engn BE-3001 Leuven Belgium Univ Ferrara Engn Dept ENDIF I-44122 Ferrara Italy CNRS AIST JRL RL UMI3218 Tsukuba Ibaraki 3058568 Japan Univ Montpellier CNRS LIRMM Interact Digital Human Montpellier France Eindhoven Univ Technol Dept Mech Engn NL-5612 AZ Eindhoven Netherlands

The problem of robotic task definition and execution was pioneered by Mason, who defined setpoint constraints where the position, velocity, and/or forces are expressed in one particular task frame for a 6-DOF robot. Later extensions generalized this approach to constraints in 1) multiple frames;2) redundant robots;3) other sensor spaces such as cameras;and 4) trajectory tracking. Our work extends tasks definition to 1) expressions of constraints, with a focus on expressions between geometric entities ( distances and angles), in place of explicit set-point constraints;2) a systematic composition of constraints;3) runtime monitoring of all constraints ( that allows for runtime sequencing of constraint sets via, for example, a Finite State Machine);and 4) formal task descriptions, that can be used by symbolic reasoners to plan and analyse tasks. This means that tasks are seen as ordered groups of constraints to be achieved by the robot's motion controller, possibly with different set of geometric expressions to measure outputs, which are not controlled, but are relevant to assess the task evolution. Those monitored expressionsmay result in events that trigger switching to another ordered group of constraints to execute and monitor. For these task specifications, formal language definitions are introduced in the JSON-schema modeling language.

关键词： Software middleware and programming environments Motion and Path Planning Behaviour-Based Systems

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Context-Aware Task Handling in Resource-Constrained Robots with Virtualization 7

Context-Aware Task Handling in Resource-Constrained Robots w...

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7th IEEE International Conference on Edge Computing and Communications (IEEE EDGE) / IEEE World Congress on Services (SERVICES)

作者： Hadidi, Ramyad Ghaleshahi, Nima Shoghi Asgari, Bahar Kim, Hyesoon Rain AI Atlanta GA 30302 USA Georgia Tech Atlanta GA USA Univ Maryland College Pk MD USA

ISBN: (纸本)9798350304831

Intelligent mobile robots are critical in several scenarios. However, as their computational resources are limited, mobile robots struggle to handle several tasks concurrently while guaranteeing real timeliness. To address this challenge and improve the real-timeliness of critical tasks under resource constraints, we propose a fast context-aware task handling technique. To effectively handle tasks in real-time, our proposed context-aware technique comprises three main ingredients: (i) a dynamic time-sharing mechanism, coupled with (ii) an event-driven task scheduling using reactive programming paradigm to mindfully use the limited resources;and, (iii) a lightweight virtualized execution to easily integrate functionalities and their dependencies. We showcase our technique on a Raspberry-Pi-based robot with a variety of tasks such as Simultaneous localization and mapping (SLAM), sign detection, and speech recognition with a 42% speedup in total execution time compared to the common Linux scheduler.

关键词： Edge AI Software Mobile Robots middleware and programming environments Reactive and Sensor-Based Planning

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