Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm

Redundant manipulators play important roles in many industrial and service applications by assisting people fulfill heavy and repetitive jobs. However, redundant manipulators are coupled highly-nonlinear systems which exert difficulty of redundancy resolution computation. Conventional methods such as pseudo-inverse-based approaches obtain the resolved joint angles from joint velocity level, which may bring about more computational cost and may neglect joint velocity limits. In this work, a motion planning method based on beetle antennae search algorithm (BAS) is proposed for motion planning of redundant manipulators with the variable joint velocity limit. Such proposed work does not need to resolve the velocity kinematics equation as the conventional methods do, and the proposed method can directly deal with the forward kinematics equation to resolve the desired joint angles. The simulation and experiment on the five-link planar manipulator and the Kuka industrial manipulator system demonstrate the efficiency of the proposed method for motion planning of redundant manipulator, and reveal the reliable performance of the BAS algorithm as compared with genetic algorithm (GA), particle swarm optimization (PSO), firefly algorithm(FA) and quantum behaved particle swarm algorithm(QPSO) methods

SELF-COLLISION AVOIDANCE OF ARM ROBOT USING GENERATIVE ADVERSARIAL NETWORK AND PARTICLES SWARM OPTIMIZATION (GAN-PSO)

Collision avoidance of Arm Robot is designed for the robot to collide objects, colliding environment, and colliding its body. Self-collision avoidance was successfully trained using Generative Adversarial Networks (GANs) and Particle Swarm Optimization (PSO). The Inverse Kinematics (IK) with 96K motion data was extracted as the dataset to train data distribution of  3.6K samples and 7.2K samples. The proposed method GANs-PSO can solve the common GAN problem such as Mode Collapse or Helvetica Scenario that occurs when the generator  always gets the same output point which mapped to different input  values. The discriminator  produces the random samples' data distribution in which present the real data distribution (generated by Inverse Kinematic analysis).  The PSO was successfully reduced the number of training epochs of the generator  only with 5000 iterations. The result of our proposed method (GANs-PSO) with 50 particles was 5000 training epochs executed in 0.028ms per single prediction and 0.027474% Generator Mean Square Error (GMSE)

Synthesis of the Inverse Kinematic Model of Non-Redundant Open-Chain Robotic Systems Using Groebner Basis Theory

[EN] One of the most important elements of a robot's control system is its Inverse Kinematic Model (IKM), which calculates the position and velocity references required by the robot's actuators to follow a trajectory. The methods that are commonly used to synthesize the IKM of open-chain robotic systems strongly depend on the geometry of the analyzed robot. Those methods are not systematic procedures that could be applied equally in all possible cases. This project presents the development of a systematic procedure to synthesize the IKM of non-redundant open-chain robotic systems using Groebner Basis theory, which does not depend on the geometry of the robot's structure. The inputs to the developed procedure are the robot's Denavit-Hartenberg parameters, while the output is the IKM, ready to be used in the robot's control system or in a simulation of its behavior. The Groebner Basis calculation is done in a two-step process, first computing a basis with Faugere's F4 algorithm and a grevlex monomial order, and later changing the basis with the FGLM algorithm to the desired lexicographic order. This procedure's performance was proved calculating the IKM of a PUMA manipulator and a walking hexapod robot. The errors in the computed references of both IKMs were absolutely negligible in their corresponding workspaces, and their computation times were comparable to those required by the kinematic models calculated by traditional methods. The developed procedure can be applied to all Cartesian robotic systems, SCARA robots, all the non-redundant robotic manipulators that satisfy the in-line wrist condition, and any non-redundant open-chain robot whose IKM should only solve the positioning problem, such as multi-legged walking robots.This research was partially funded by Plan Nacional de I+D+i, Agencia Estatal de Investigacion del Ministerio de Economia, Industria y Competitividad del Gobierno de Espana, in the project FEDER-CICYT DPI2017-84201-R.Guzmán-Giménez, J.; Valera Fernández, Á.; Mata Amela, V.; Díaz-Rodríguez, MÁ. (2020). Synthesis of the Inverse Kinematic Model of Non-Redundant Open-Chain Robotic Systems Using Groebner Basis Theory. Applied Sciences. 10(8):1-22. https://doi.org/10.3390/app10082781S122108Atique, M. M. U., Sarker, M. R. I., & Ahad, M. A. R. (2018). Development of an 8DOF quadruped robot and implementation of Inverse Kinematics using Denavit-Hartenberg convention. Heliyon, 4(12), e01053. doi:10.1016/j.heliyon.2018.e01053Flanders, M., & Kavanagh, R. C. (2015). Build-A-Robot: Using virtual reality to visualize the Denavit-Hartenberg parameters. Computer Applications in Engineering Education, 23(6), 846-853. doi:10.1002/cae.21656Özgür, E., & Mezouar, Y. (2016). Kinematic modeling and control of a robot arm using unit dual quaternions. Robotics and Autonomous Systems, 77, 66-73. doi:10.1016/j.robot.2015.12.005Wang, X., Han, D., Yu, C., & Zheng, Z. (2012). The geometric structure of unit dual quaternion with application in kinematic control. Journal of Mathematical Analysis and Applications, 389(2), 1352-1364. doi:10.1016/j.jmaa.2012.01.016Barrientos, A., Álvarez, M., Hernández, J. D., del Cerro, J., & Rossi, C. (2012). Modelado de Caden as Cinemáticas mediante Matrices de Desplazamiento. Una alternativa al método de Denavit-Hartenberg. Revista Iberoamericana de Automática e Informática Industrial RIAI, 9(4), 371-382. doi:10.1016/j.riai.2012.09.004Virgil Petrescu, R. V., Aversa, R., Apicella, A., Mirsayar, M., Kozaitis, S., Abu-Lebdeh, T., & Tiberiu Petrescu, F. I. (2017). Geometry and Inverse Kinematic at the MP3R Mobile Systems. Journal of Mechatronics and Robotics, 1(2), 58-65. doi:10.3844/jmrsp.2017.58.65Chen, S., Luo, M., Abdelaziz, O., & Jiang, G. (2017). A general analytical algorithm for collaborative robot (cobot) with 6 degree of freedom (DOF). 2017 International Conference on Applied System Innovation (ICASI). doi:10.1109/icasi.2017.7988522Bouzgou, K., & Ahmed-Foitih, Z. (2014). Geometric modeling and singularity of 6 DOF Fanuc 200IC robot. Fourth edition of the International Conference on the Innovative Computing Technology (INTECH 2014). doi:10.1109/intech.2014.6927745Mahajan, A., Singh, H. P., & Sukavanam, N. (2017). An unsupervised learning based neural network approach for a robotic manipulator. International Journal of Information Technology, 9(1), 1-6. doi:10.1007/s41870-017-0002-2Duka, A.-V. (2014). Neural Network based Inverse Kinematics Solution for Trajectory Tracking of a Robotic Arm. Procedia Technology, 12, 20-27. doi:10.1016/j.protcy.2013.12.451Toshani, H., & Farrokhi, M. (2014). Real-time inverse kinematics of redundant manipulators using neural networks and quadratic programming: A Lyapunov-based approach. Robotics and Autonomous Systems, 62(6), 766-781. doi:10.1016/j.robot.2014.02.005Rokbani, N., & Alimi, A. M. (2013). Inverse Kinematics Using Particle Swarm Optimization, A Statistical Analysis. Procedia Engineering, 64, 1602-1611. doi:10.1016/j.proeng.2013.09.242Jiang, G., Luo, M., Bai, K., & Chen, S. (2017). A Precise Positioning Method for a Puncture Robot Based on a PSO-Optimized BP Neural Network Algorithm. Applied Sciences, 7(10), 969. doi:10.3390/app7100969Köker, R. (2013). A genetic algorithm approach to a neural-network-based inverse kinematics solution of robotic manipulators based on error minimization. Information Sciences, 222, 528-543. doi:10.1016/j.ins.2012.07.051Rokbani, N., Casals, A., & Alimi, A. M. (2014). IK-FA, a New Heuristic Inverse Kinematics Solver Using Firefly Algorithm. Computational Intelligence Applications in Modeling and Control, 369-395. doi:10.1007/978-3-319-11017-2_15Buchberger, B. (2001). Multidimensional Systems and Signal Processing, 12(3/4), 223-251. doi:10.1023/a:1011949421611Kendricks, K. D. (2013). A kinematic analysis of the gmf a-510 robot: An introduction and application of groebner basis theory. Journal of Interdisciplinary Mathematics, 16(2-03), 147-169. doi:10.1080/09720502.2013.800304Wang, Y., Hang, L., & Yang, T. (2006). Inverse Kinematics Analysis of General 6R Serial Robot Mechanism Based on Groebner Base. Frontiers of Mechanical Engineering in China, 1(1), 115-124. doi:10.1007/s11465-005-0022-7Abbasnejad, G., & Carricato, M. (2015). Direct Geometrico-static Problem of Underconstrained Cable-Driven Parallel Robots With $n$ Cables. IEEE Transactions on Robotics, 31(2), 468-478. doi:10.1109/tro.2015.2393173Rameau, J.-F., & Serré, P. (2015). Computing mobility condition using Groebner basis. Mechanism and Machine Theory, 91, 21-38. doi:10.1016/j.mechmachtheory.2015.04.003Xiguang Huang, & Guangpin He. (2009). Forward kinematics of the general Stewart-Gough platform using Gröbner basis. 2009 International Conference on Mechatronics and Automation. doi:10.1109/icma.2009.5246088Uchida, T., & McPhee, J. (2012). Using Gröbner bases to generate efficient kinematic solutions for the dynamic simulation of multi-loop mechanisms. Mechanism and Machine Theory, 52, 144-157. doi:10.1016/j.mechmachtheory.2012.01.015Faugère, J.-C. (2010). FGb: A Library for Computing Gröbner Bases. Lecture Notes in Computer Science, 84-87. doi:10.1007/978-3-642-15582-6_17Faugére, J.-C. (1999). A new efficient algorithm for computing Gröbner bases (F4). Journal of Pure and Applied Algebra, 139(1-3), 61-88. doi:10.1016/s0022-4049(99)00005-5Faugère, J. C., Gianni, P., Lazard, D., & Mora, T. (1993). Efficient Computation of Zero-dimensional Gröbner Bases by Change of Ordering. Journal of Symbolic Computation, 16(4), 329-344. doi:10.1006/jsco.1993.1051Salzer, H. E. (1960). A note on the solution of quartic equations. Mathematics of Computation, 14(71), 279-279. doi:10.1090/s0025-5718-1960-0117882-

Use Improved Differential Evolution Algorithms to Handle the Inverse Kinetics Problem for Robots with Residual Degrees of Freedom

In this study, the Self-adaptive strategy algorithm for controlling parameters in Differential Evolution algorithm (ISADE) improved from the Differential Evolution (DE) algorithm, as well as the upgraded version of the algorithms has been applied to solve the Inverse Kinetics (IK) problem for the redundant robot with 7 Degree of Freedom (DoF). The results were compared with 4 other algorithms of DE and Particle Swarm Optimization (PSO) as well as Pro-DE and Pro-PSO algorithms. These algorithms are tested in three different Scenarios for the motion trajectory of the end effector of in the workspace. In the first scenario, the IK results for a single point were obtained. 100 points randomly generated in the robot’s workspace was input parameters for Scenario 2, while Scenario 3 used 100 points located on a spline in the robot workspace. The algorithms were compared with each other based on the following criteria: execution time, endpoint distance error, number of generations required and especially quality of the joints’ variable found. The comparison results showed 2 main points: firstly, the ISADE algorithm gave much better results than the other DE and PSO algorithms based on the criteria of execution time, endpoint accuracy and generation number required. The second point is that when applying Pro-ISADE, Pro-DE and Pro-PSO algorithms, in addition to the ability to significantly improve the above parameters compared to the ISADE, DE and PSO algorithms, it also ensures the quality of solved joints’ values

Automatic selection of the Groebner Basis' monomial order employed for the synthesis of the inverse kinematic model of non-redundant open-chain robotic systems

This is an Author's Accepted Manuscript of an article published in José Guzmán-Giménez, Ángel Valera Fernández, Vicente Mata Amela & Miguel Ángel Díaz-Rodríguez (2023) Automatic selection of the Groebner Basis¿ monomial order employed for the synthesis of the inverse kinematic model of non-redundant open-chain robotic systems, Mechanics Based Design of Structures and Machines, 51:5, 2458-2480, DOI: 10.1080/15397734.2021.1899829 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/15397734.2021.1899829[EN] The methods most commonly used to synthesize the Inverse Kinematic Model (IKM) of open-chain robotic systems strongly depend on the robot's geometry, which make them difficult to systematize. In a previous work we presented a systematic procedure that relies on Groebner Bases to synthesize the IKM of non-redundant open-chain robots. This study expands the developed procedure with a methodology for the automatic selection of the basis' monomial order. The procedure's inputs are the robot's Denavit-Hartenberg parameters and the movement range of its actuators, while the output is the synthesized IKM, ready to be used in the robot's control system or in a simulation of its behavior. This procedure can synthesize the IKM of a wide range of open-chain robotic systems, such as Cartesian robots, SCARA, non-redundant multi-legged robots, and all non-redundant manipulators that satisfy the in-line wrist condition. The procedure's performance is assessed through two study cases of open-chain robots: a walking hexapod and a PUMA manipulator. The optimal monomial order is successfully identified for all cases. Also the output errors of the synthesized IKMs are negligible when evaluated in their corresponding workspaces, while their computation times are comparable to those required by the kinematic models calculated by traditional methods.This research was partially funded by Plan Nacional de IthornDthorni, Agencia Estatal de Investigacion del Ministerio de Economia, Industria y Competitividad del Gobierno de Espana, in the project FEDER-CICYT DPI201784201-R.Guzmán-Giménez, J.; Valera Fernández, Á.; Mata Amela, V.; Díaz-Rodríguez, MÁ. (2023). Automatic selection of the Groebner Basis' monomial order employed for the synthesis of the inverse kinematic model of non-redundant open-chain robotic systems. Mechanics Based Design of Structures and Machines. 51(5):2458-2480. https://doi.org/10.1080/15397734.2021.18998292458248051

Advances in Spacecraft Attitude Control

Spacecraft attitude maneuvers comply with Euler's moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research. This book is meant for basic scientifically inclined readers, and commences with a chapter on the basics of spaceflight and leverages this remediation to reveal very advanced topics to new spaceflight enthusiasts. The topics learned from reading this text will prepare students and faculties to investigate interesting spaceflight problems in an era where cube satellites have made such investigations attainable by even small universities. It is the fondest hope of the editor and authors that readers enjoy this book

A first approach to a proposal of a soft robotic link acting as a neck

[Abstract] The purpose of this paper is to design a soft robotic neck prototype with two Degrees of Freedom (DOF) and propose a control system based on a fractional order PD controller (FPD). The neck will be able to perform movements of flexion, extension and lateral bending. To achieve these movements, the design is made based on a cable-driven mechanism, with components easy to manufacture in a 3D printer. Simulations are performed to validate the feasibility of the developed parallel robot prototype and the robustness of the proposed control scheme to mass changes at the tip.Ministerio de Economía y Empresa; DPI2016-75330-

A model-based approach to robot kinematics and control using discrete factor graphs with belief propagation

Much of recent researches in robotics have shifted the focus from traditionally-specific industrial tasks to investigations of new types of robots with alternative ways of controlling them. In this paper, we describe the development of a generic method based on factor graphs to model robot kinematics. We focused on the kinematics aspect of robot control because it provides a fast and systematic solution for the robot agent to move in a dynamic environment. We developed neurally-inspired factor graph models that can be applied on two different robotic systems: a mobile platform and a robotic arm. We also demonstrated that we can extend the static model of the robotic arm into a dynamic model useful for imitating natural movements of a human hand. We tested our methods in a simulation environment as well as in scenarios involving real robots. The experimental results proved the flexibility of our proposed methods in terms of remodeling and learning, which enabled the modeled robot to perform reliably during the execution of given tasks

Advances in Spacecraft Attitude Control

Spacecraft attitude maneuvers comply with Euler's moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research. This book is meant for basic scientifically inclined readers, and commences with a chapter on the basics of spaceflight and leverages this remediation to reveal very advanced topics to new spaceflight enthusiasts. The topics learned from reading this text will prepare students and faculties to investigate interesting spaceflight problems in an era where cube satellites have made such investigations attainable by even small universities. It is the fondest hope of the editor and authors that readers enjoy this book

High-precision grasping and placing for mobile robots

This work presents a manipulation system for multiple labware in life science laboratories using the H20 mobile robots. The H20 robot is equipped with the Kinect V2 sensor to identify and estimate the position of the required labware on the workbench. The local features recognition based on SURF algorithm is used. The recognition process is performed for the labware to be grasped and for the workbench holder. Different grippers and labware containers are designed to manipulate different weights of labware and to realize a safe transportation