Real-time trajectory planning based on joint-decoupled optimization in human-robot interaction

Zhang, Shiyu; Zanchettin, Andrea Maria; Villa, Renzo; Dai, Shi‐Lu

doi:10.1016/j.mechmachtheory.2019.103664

Cited by 21 publications

(8 citation statements)

References 23 publications

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“…Trajectory planning in Cartesian space is intuitive, and the movement trajectory and attitude of the end-effector are easy to observe. But, this method did not consider problems caused by kinematic singularities [1][2][3][4]. Trajectory planning in joint space can avoid those problems.…”

Section: Introductionmentioning

confidence: 99%

Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Wang

Xin

Miao

et al. 2020

Mathematical Problems in Engineering

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Robot will be used in the grinding industry widely to liberate human beings from harsh environments. In the grinding process, optimal trajectory planning will not only improve the processing quality but also improve the machining efficiency. The aims of this study are to propose a new algorithm and verify its efficiency in achieving the optimal trajectory planning of the grinding robot. An objective function has been defined terms of both time and jerk. Improved whale optimization algorithm (IWOA) is proposed based on whale optimization algorithm (WOA) and differential evolution algorithm (DE). Mutation operation and selection operation of DE are imitated in the part of initialization to process the population initialized by WOA, and then, the search tasks of WOA are performed. Motion with a constant velocity of the end-effector is considered during fine grinding. The continuity of acceleration and velocity will be achieved by minimizing jerk, and at the same time, smooth robot movement can be obtained. Cubic spline interpolation is implemented. A six-axis industrial robot is used for this research. Results show that optimal trajectory planning based on IWOA is more efficient than others. This method presented in this paper may have some indirect significance in robot business.

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Section: Introductionmentioning

confidence: 99%

Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Wang

Xin

Miao

et al. 2020

Mathematical Problems in Engineering

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“…At every cycle, the high-speed motions are restored as soon as the safety issue is resolved. Non-linear optimization problems in real-time are presented in [61], where the trajectory planning problem is solved by using a decoupling method that transforms the original coupled optimization problem into multiple independent optimization problems, to reduce the computational burden. A non-linear programming problem (NLP) with human-in-the-loop constraints is also solved in the reference [62] in order to optimize the desired path subdivided into multiple segments.…”

Section: Motion Planningmentioning

confidence: 99%

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

Proia

Carli

Cavone

et al. 2022

IEEE Trans. Automat. Sci. Eng.

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The fourth industrial revolution, also known as Industry 4.0, is reshaping the way individuals live and work while providing a substantial influence on the manufacturing scenario.The key enabling technology that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of employees' safety and well-being, together with the increase of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this paper presents an accurate review of the most recent and relevant contributions to the related literature, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and the promising future developments in the context of the digital evolution.Note to Practitioners-The design and development of manufacturing systems are experiencing substantial changes towards full automation. This ongoing challenge is being tackled by academia and industrial practitioners with the adoption of collaborative robots, where the skills and peculiarities of humans (e.g., intelligence, creativity, adaptability, etc.) and robots (e.g., flexibility, pinpoint accuracy, tirelessness, etc.) are combined to better perform a variety of tasks. Nevertheless, due to their different characteristics, there is an emerging need for designing suitable decision and control techniques to ensure a safe and ergonomic HRC, while keeping the highest level of productivity. Against this background, the aim of this paper is to provide researchers and practitioners with a reference source in the related field, which can help them designing and developing suitable solutions to control problems in safe, ergonomic, and efficient collaborative robotics.

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“…Since the task of designing a fast motion function is so elementary, a considerable number of research articles have appeared, particularly in the last two decades. This work can roughly be organized into two classes: in the first one, the task has been formulated as a restricted optimization problem, and algorithms from this field have been applied (e.g., [15][16][17][18][19][20][21][22][23][24][25]). This approach has the advantage that other aspects such as position errors regarding a given path or energy consumption can be easily included, and even a multiobjective optimization can be performed [22].…”

Section: Introductionmentioning

confidence: 99%

On Fast Jerk-Continuous Motion Functions with Higher-Order Kinematic Restrictions for Online Trajectory Generation

Alpers

2022

Robotics

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In robotics and automated manufacturing, motion functions for parts of machines need to be designed. Many proposals for the shape of such functions can be found in the literature. Very often, time efficiency is a major criterion for evaluating the suitability for a given task. If there are higher precision requirements, the reduction in vibration also plays a major role. In this case, motion functions should have a continuous jerk function but still be as fast as possible within the limits of kinematic restrictions. The currently available motion designs all include assumptions that facilitate the computation but are unnecessary and lead to slower functions. In this contribution, we drop these assumptions and provide an algorithm for computing a jerk-continuous fifteen segment profile with arbitrary initial and final velocities where given kinematic restrictions are met. We proceed by going systematically through the design space using the concept of a varying intermediate velocity and identify critical velocities and jerks where one has to switch models. The systematic approach guarantees that all possible situations are covered. We implemented and validated the model using a huge number of random configurations in Matlab, and we show that the algorithm is fast enough for online trajectory generation. Examples illustrate the improvement in time efficiency compared to existing approaches for a wide range of configurations where the maximum velocity is not held over a period of time. We conclude that faster motion functions are possible at the price of an increase in complexity, yet which is still manageable.

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Real-time trajectory planning based on joint-decoupled optimization in human-robot interaction

Cited by 21 publications

References 23 publications

Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

On Fast Jerk-Continuous Motion Functions with Higher-Order Kinematic Restrictions for Online Trajectory Generation

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