Trajectory planning for industrial robot using genetic algorithms

En las últimas décadas, debido la importancia de sus aplicaciones, se han propuesto muchas investigaciones sobre la planificación de caminos y trayectorias para los manipuladores, algunos de los ámbitos en los que pueden encontrarse ejemplos de aplicación son; la robótica industrial, sistemas autónomos, creación de prototipos virtuales y diseño de fármacos asistido por ordenador. Por otro lado, los algoritmos evolutivos se han aplicado en muchos campos, lo que motiva el interés del autor por investigar sobre su aplicación a la planificación de caminos y trayectorias en robots industriales. En este trabajo se ha llevado a cabo una búsqueda exhaustiva de la literatura existente relacionada con la tesis, que ha servido para crear una completa base de datos utilizada para realizar un examen detallado de la evolución histórica desde sus orígenes al estado actual de la técnica y las últimas tendencias. Esta tesis presenta una nueva metodología que utiliza algoritmos genéticos para desarrollar y evaluar técnicas para la planificación de caminos y trayectorias. El conocimiento de problemas específicos y el conocimiento heurístico se incorporan a la codificación, la evaluación y los operadores genéticos del algoritmo. Esta metodología introduce nuevos enfoques con el objetivo de resolver el problema de la planificación de caminos y la planificación de trayectorias para sistemas robóticos industriales que operan en entornos 3D con obstáculos estáticos, y que ha llevado a la creación de dos algoritmos (de alguna manera similares, con algunas variaciones), que son capaces de resolver los problemas de planificación mencionados. El modelado de los obstáculos se ha realizado mediante el uso de combinaciones de objetos geométricos simples (esferas, cilindros, y los planos), de modo que se obtiene un algoritmo eficiente para la prevención de colisiones. El algoritmo de planificación de caminos se basa en técnicas de optimización globales, usando algoritmos genéticos para minimizar una función objetivo considerando restricciones para evitar las colisiones con los obstáculos. El camino está compuesto de configuraciones adyacentes obtenidas mediante una técnica de optimización construida con algoritmos genéticos, buscando minimizar una función multiobjetivo donde intervienen la distancia entre los puntos significativos de las dos configuraciones adyacentes, así como la distancia desde los puntos de la configuración actual a la final. El planteamiento del problema mediante algoritmos genéticos requiere de una modelización acorde al procedimiento, definiendo los individuos y operadores capaces de proporcionar soluciones eficientes para el problema.Abu-Dakka, FJM. (2011). Trajectory planning for industrial robot using genetic algorithms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10294Palanci

Integrated Trajectory-Tracking and Vibration Control of Kinematically-Constrained Warehousing Cable Robots

With the explosion of e-commerce in recent years, there is a strong desire for automated material handling solutions including warehousing robots. Cable driven parallel robots (CDPRs) are a relatively new concept which has yet to be explored for high-speed pick-&-place applications in the industry. Compared to rigid-link parallel robots, a CDPR possesses significant advantages including: large workspace, low moving inertia, high-speed motion, low power consumption, and incurring minimal maintenance cost. On the other hand, the main disadvantages of the CDPRs are the cable’s unilateral force exerting capability and low rigidity which is resulting in undesired vibrations of their moving platform. Kinematically-constrained CDPRs (KC-CDPRs) include a special class of CDPRs which provide a considerably higher level of stiffness in undesired degrees of freedom (DOFs) via connecting a set of constrained cables to the same actuator. Nevertheless, undesired vibrations of the moving platform are still their main problem which request more attention and investigation. Dynamic modeling, stiffness optimization, vibration and trajectory-tracking control, and stiffness-based trajectory-planning of redundant KC-CDPRs are studied in this thesis. As a new technique, we separate the moving platform’s vibration equations from its desired (nominal) equations of motion. The obtained vibration model forms a linear parametric variable (LPV) dynamic system which is based for the following contributions: 1) Proposing a new tension optimization approach to minimize undesired perturbations under external disturbances in a desired direction; and demonstrating the effectiveness of kinematically-constrained actuation method in vibration attenuation of CDPRs in undesired DOFs. 2) Providing the opportunity of using a wide class of well-established robust and optimal LPV-based control methods, such as H∞ control techniques, for trajectory-tracking control of CDPRs to minimize the effect of disturbances on the robot operation; and showing the effectiveness of kinematically-constrained actuation method in control design simplification of such robots. 3) Proposing the concept of stiffness-based trajectory-planning to find the stiffness-optimum geometry of trajectories for KC-CDPRs; and designing a time-optimal zero-to-zero continuous-jerk motion to track such trajectories. All the proposed concepts are developed for a generic KC-CDPR and verified via numerical analysis and experimental tests of a real planar warehousing KC-CDPR

Low Mobility Cable Robot with Application to Robotic Warehousing

Cable-based robots consist of a rigid mobile platform connected via flexible links (cables, wires, tendons) to a surrounding static platform. The use of cables simplifies the mechanical structure and reduces the inertia, allowing the mobile platform to reach high motion acceleration in large workspaces. These attributes give, in principle, an advantage over conventional robots used for industrial applications, such as the pick and place of objects inside factories or similar exterior large workspaces. However, unique cable properties involve new theoretical and technical challenges: all cables must be in tension to avoid collapse of the mobile platform. In addition, positive tensions applied to cables may affect the overall stiffness, that is, cable stretch might result in unacceptable oscillations of the mobile platform. Fully constrained cable-based robots can be distinguished from other types of cable-based robots because the motion and force generation of the mobile platform is accomplished by controlling both the cable lengths and the positive cable tensions. Fully constrained cable-based robots depend on actuator redundancy, that is, the addition of one or more actuated cables than end-effector degrees of freedom. Redundancy has proved to be beneficial to expand the workspace, remove some types of singularities, increase the overall stiffness, and support high payloads in several proposed cable-based robot designs. Nevertheless, this strategy demands the development of efficient controller designs for real-time applications. This research deals with the design and control of a fully constrained cable-based parallel manipulator for large-scale high-speed warehousing applications. To accomplish the design of the robot, a well-ordered procedure to analyze the cable tensions, stiffness and workspace will be presented to obtain an optimum structure. Then, the control problem will be investigated to deal with the redundancy solution and all-positive cable tension condition. The proposed control method will be evaluated through simulation and experimentation in a prototype manufactured for testing

Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques

Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques