{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T12:15:39Z","timestamp":1775564139155,"version":"3.50.1"},"reference-count":22,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2012,1,6]],"date-time":"2012-01-06T00:00:00Z","timestamp":1325808000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,1,6]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to analyze the impact of the torque, power, jerk and energy consumed constraints on the generation of minimum time collision\u2010free trajectories for industrial robots in a complex environment.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>An algorithm is presented in which the trajectory is generated under real working constraints (specifically torque, power, jerk and energy consumed). It also takes into account the presence of obstacles (to avoid collisions) and the dynamics of the robotic system. The method solves an optimization problem to find the minimum time trajectory to perform the tasks the robot should do.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Important conclusions have been reached when solving the trajectory planning problem related to the value of the torque, power, jerk and energy consumed and the relationship between them, therefore enabling the user to choose the most efficient way of working depending on which parameter he is most interested in optimizing. From the examples solved the authors have found the relationship between the maximum and minimum values of the parameters studied.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>This new approach tries to model the real behaviour of the actuators in order to be able to upgrade the trajectory quality, so a lot of work has to be done in this field.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The algorithm solves the trajectory planning problem for any industrial robot and the real characteristics of the actuators are taken into account, which is essential to improve the performance of it.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>This new tool enables the performance of the robot to be improved by combining adequately the values of the mentioned parameters (torque, power, jerk and consumed energy).<\/jats:p><\/jats:sec>","DOI":"10.1108\/01439911211192538","type":"journal-article","created":{"date-parts":[[2012,1,14]],"date-time":"2012-01-14T07:14:27Z","timestamp":1326525267000},"page":"92-100","source":"Crossref","is-referenced-by-count":26,"title":["Optimal time trajectories for industrial robots with torque, power, jerk and energy consumed constraints"],"prefix":"10.1108","volume":"39","author":[{"given":"Francisco","family":"Rubio","sequence":"first","affiliation":[]},{"given":"Francisco","family":"Valero","sequence":"additional","affiliation":[]},{"given":"Joseph","family":"Sunyer","sequence":"additional","affiliation":[]},{"given":"Juan","family":"Cuadrado","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022021220413302000_b1","doi-asserted-by":"crossref","unstructured":"Bobrow, J.E., Dubowsky, S. and Gibson, J.S. 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