A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings. Palmieri, J., Di Lillo, P., Lippi, M., Chiaverini, S., & Marino, A. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024. ![A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex This paper introduces a control architecture that enables a robotic system to ensure the safety of human operators entering its workspace. The proposed method utilizes an appropriate metric to measure safety levels and adjusts the robot’s motion to maintain this metric above a minimum threshold. To guarantee safety, the robot scales down and deviates from its intended path. For redundant robots, internal motion is exploited to enhance safety levels further. The approach is incorporated into a Hierarchical Quadratic Programming control framework, allowing the robot to address other control objectives simultaneously, such as handling joint limits. Experimental results with a dual-arm mobile robot developed as part of the EU-funded CANOPIES project demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper was motivated by the problem of ensuring human safety in unstructured environments shared with human operators. We propose a control architecture that allows complex dual-arm robotic systems to operate effectively in such scenarios. The devised architecture gives the robot the capability to slow down a trajectory to follow as well as to deviate from a nominal path to keep a human operator safe. We tested the devised approach in a precision farming setting; however, it can be adopted in any human-robot interaction scenario.
@article{
11580_106932,
author = {Palmieri, Jozsef and Di Lillo, Paolo and Lippi, Martina and Chiaverini, Stefano and Marino, Alessandro},
title = {A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings},
year = {2024},
journal = {IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING},
abstract = {This paper introduces a control architecture that enables a robotic system to ensure the safety of human operators entering its workspace. The proposed method utilizes an appropriate metric to measure safety levels and adjusts the robot’s motion to maintain this metric above a minimum threshold. To guarantee safety, the robot scales down and deviates from its intended path. For redundant robots, internal motion is exploited to enhance safety levels further. The approach is incorporated into a Hierarchical Quadratic Programming control framework, allowing the robot to address other control objectives simultaneously, such as handling joint limits. Experimental results with a dual-arm mobile robot developed as part of the EU-funded CANOPIES project demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper was motivated by the problem of ensuring human safety in unstructured environments shared with human operators. We propose a control architecture that allows complex dual-arm robotic systems to operate effectively in such scenarios. The devised architecture gives the robot the capability to slow down a trajectory to follow as well as to deviate from a nominal path to keep a human operator safe. We tested the devised approach in a precision farming setting; however, it can be adopted in any human-robot interaction scenario.},
keywords = {Human–robot interaction, human safety, dual-arm system, trajectory scaling, path modification, precision agriculture},
url = {https://ieeexplore.ieee.org/document/10413980},
doi = {10.1109/TASE.2024.3350976}
}
Downloads: 0
{"_id":"JEqzPBgpMrNzG2YK7","bibbaseid":"palmieri-dilillo-lippi-chiaverini-marino-acontrolarchitectureforsafetrajectorygenerationinhumanrobotcollaborativesettings-2024","author_short":["Palmieri, J.","Di Lillo, P.","Lippi, M.","Chiaverini, S.","Marino, A."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Palmieri"],"firstnames":["Jozsef"],"suffixes":[]},{"propositions":[],"lastnames":["Di","Lillo"],"firstnames":["Paolo"],"suffixes":[]},{"propositions":[],"lastnames":["Lippi"],"firstnames":["Martina"],"suffixes":[]},{"propositions":[],"lastnames":["Chiaverini"],"firstnames":["Stefano"],"suffixes":[]},{"propositions":[],"lastnames":["Marino"],"firstnames":["Alessandro"],"suffixes":[]}],"title":"A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings","year":"2024","journal":"IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING","abstract":"This paper introduces a control architecture that enables a robotic system to ensure the safety of human operators entering its workspace. The proposed method utilizes an appropriate metric to measure safety levels and adjusts the robot’s motion to maintain this metric above a minimum threshold. To guarantee safety, the robot scales down and deviates from its intended path. For redundant robots, internal motion is exploited to enhance safety levels further. The approach is incorporated into a Hierarchical Quadratic Programming control framework, allowing the robot to address other control objectives simultaneously, such as handling joint limits. Experimental results with a dual-arm mobile robot developed as part of the EU-funded CANOPIES project demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper was motivated by the problem of ensuring human safety in unstructured environments shared with human operators. We propose a control architecture that allows complex dual-arm robotic systems to operate effectively in such scenarios. The devised architecture gives the robot the capability to slow down a trajectory to follow as well as to deviate from a nominal path to keep a human operator safe. We tested the devised approach in a precision farming setting; however, it can be adopted in any human-robot interaction scenario.","keywords":"Human–robot interaction, human safety, dual-arm system, trajectory scaling, path modification, precision agriculture","url":"https://ieeexplore.ieee.org/document/10413980","doi":"10.1109/TASE.2024.3350976","bibtex":"@article{\n\t11580_106932,\n\tauthor = {Palmieri, Jozsef and Di Lillo, Paolo and Lippi, Martina and Chiaverini, Stefano and Marino, Alessandro},\n\ttitle = {A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings},\n\tyear = {2024},\n\tjournal = {IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING},\n\tabstract = {This paper introduces a control architecture that enables a robotic system to ensure the safety of human operators entering its workspace. The proposed method utilizes an appropriate metric to measure safety levels and adjusts the robot’s motion to maintain this metric above a minimum threshold. To guarantee safety, the robot scales down and deviates from its intended path. For redundant robots, internal motion is exploited to enhance safety levels further. The approach is incorporated into a Hierarchical Quadratic Programming control framework, allowing the robot to address other control objectives simultaneously, such as handling joint limits. Experimental results with a dual-arm mobile robot developed as part of the EU-funded CANOPIES project demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper was motivated by the problem of ensuring human safety in unstructured environments shared with human operators. We propose a control architecture that allows complex dual-arm robotic systems to operate effectively in such scenarios. The devised architecture gives the robot the capability to slow down a trajectory to follow as well as to deviate from a nominal path to keep a human operator safe. We tested the devised approach in a precision farming setting; however, it can be adopted in any human-robot interaction scenario.},\n\tkeywords = {Human–robot interaction, human safety, dual-arm system, trajectory scaling, path modification, precision agriculture},\n\turl = {https://ieeexplore.ieee.org/document/10413980},\n\tdoi = {10.1109/TASE.2024.3350976}\n}\n","author_short":["Palmieri, J.","Di Lillo, P.","Lippi, M.","Chiaverini, S.","Marino, A."],"key":"11580_106932","id":"11580_106932","bibbaseid":"palmieri-dilillo-lippi-chiaverini-marino-acontrolarchitectureforsafetrajectorygenerationinhumanrobotcollaborativesettings-2024","role":"author","urls":{"Paper":"https://ieeexplore.ieee.org/document/10413980"},"keyword":["Human–robot interaction","human safety","dual-arm system","trajectory scaling","path modification","precision agriculture"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/f/QK4pXGQfQ2LLK8oAW/references (1).bib","dataSources":["YYA4jfiKR2BsiLkFH","a9jNc2NyyC7d58MTq","YjpAZwNicNHANadbW","9HNP8ouNgGHQfHxfN","tzXxPwGeD2XbcAv9F","DiYuYK6M663hXLXf2","Bf4QxZjro3K8gnTY3","8fppziYBdC9WhS8pc"],"keywords":["human–robot interaction","human safety","dual-arm system","trajectory scaling","path modification","precision agriculture"],"search_terms":["control","architecture","safe","trajectory","generation","human","robot","collaborative","settings","palmieri","di lillo","lippi","chiaverini","marino"],"title":"A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings","year":2024}