Kinematically optimal hyper-redundant manipulator configurations

“Hyper-redundant” robots have a very large or infinite degree of kinematic redundancy. This paper develops new methods for determining “optimal” hyper-redundant manipulator configurations based on a continuum formulation of kinematics. This formulation uses a backbone curve model to capture the robot's essential macroscopic geometric features. The calculus of variations is used to develop differential equations, whose solution is the optimal backbone curve shape. We show that this approach is computationally efficient on a single processor, and generates solutions in O(1) time for an N degree-of-freedom manipulator when implemented in parallel on O(N) processors. For this reason, it is better suited to hyper-redundant robots than other redundancy resolution methods. Furthermore, this approach is useful for many hyper-redundant mechanical morphologies which are not handled by known methods

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

Increasing the Automation Level of Serial Robotic Manipulators with Optimal Design and Collision-free Path Control

The current hydraulic robotic manipulator mechanisms for heavy-duty machines are a mature technology, and their kinematics has been developed with a focus on the human operator maneuvering a hydraulically controlled system without numerical control input. As the trend in heavy-duty manipulators is increased automation, computer control systems are increasingly being widely used, and the requirements for robotic manipulator kinematics are different. Computer control enables a different kind of robotic manipulator kinematics, which is not optimum for direct control by a human operator, because the joint motions related to the different trajectories are not native for the human mind. Numerically controlled robotic manipulators can accept kinematics that is more efficient at doing the job expected by the customer.To increase the autonomous level of robotic manipulator, the optimal structure is not enough, but it is a part of the solution toward a fully autonomous manipulator. The control system of the manipulator is the main part of computer-controlled manipulators. A collision avoidance system plays an important role in the field of autonomous robotics. Without collision avoidance functionality, it is quite obvious that only very simple movements and tasks can be carried out automatically. With more complicated movement and manipulators, some kind of collision avoidance system is required. An unknown or changing environment increases the need for an intelligent collision avoidance system that can find a collision-free path in a dynamic environment.This thesis deals with these fundamental challenges by optimizing the serial manipulator structure for the desired task and proposing a collision avoidance control system. The basic requirement in the design of such a robotic manipulator is to make sure that all the desired task points can be achieved without singularities. These properties are difficult to achieve with the general shape and type of robotic manipulators. In this research work, a task-based kinematic synthesis approach with the proper optimization method ensures that the desired requirements can be fulfilled.To enable autonomous task execution for robotic manipulators, the control systems must have a collision avoidance system that can prevent different kinds of collisions. These collisions include self-collisions, collisions with other manipulators, collisions with obstacles, and collisions with the environment. Furthermore, there can be multiple simultaneous possible collisions that need to prevented, and the collision system must be able to handle all these collisions in real-time. In this research work, a real-time collision avoidance control approach is proposed to handle these issues. Overall, both topics, covered in this thesis, are believed to be key elements for increasing the automation of serial robotic manipulators

Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities

Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this work, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page

Optimal Constrained Planning for Complex Mechatronic Systems

This thesis focuses on the challenging problem of the optimal planning for mechatronic systems. The goal is to find strategies which maximize or minimize some cost criteria defined over a given constrained problem. The planning for mobile or industrial robots is a general framework under which several different open research issues can be found. Motion planning, in fact, involves the solution of a variety of optimality problems which range from the optimal path design to the optimal trajectory planning. Since, obviously, this is a very wide research field the scope of our analysis has been limited to three main contributions which represents the novelties proposed in this thesis. Initially, the optimal path generation problem is solved in the case of planar paths for mobile robots by using a new and powerful planning primitive recently proposed in the literature. Subsequently, the optimal path tracking problem is handled by a new control scheme able to online optimal scale any designed trajectory, which can be phisically unfeasible for the controlled system, in order to fulfill given kinematic and/or dynamic constraints. Finally, the problem of the generation of optimal controls for the minimum-time state transitions of nonlinear systems is presented and an innovative differential method is devised.La tesi tratta il problema della pianificazione ottima vincolata per sistemi meccatronici. In generale, l'obiettivo è la determinazione di strategie che minimizzino o massimizzino funzionali di costo definiti su dati problemi vincolati. Il termine di pianificazione ottima riferito a dispositivi robotici mobili o industriali individua una vasta area di ricerca all'interno della quale numerosi problemi di ottimizzazioni sono ancora indagati. La pianificazione di moto, infatti, richiede la risoluzione di una ampia varietà di problemi di ottimizzazione vincolata che spazia dalla ottima pianificazione di percorso alla pianificazione di traiettoria. Nella presente tesi, l'obiettivo di ricerca è stato limitato a tre importanti contributi innovativi. Inizialmente viene affrontato il problema della pianificazione di percorsi planari ottimi per dispositivi mobili mediante l'uso di una nuova ed estremamente versatile primitiva di pianificazione proposta in letteratura. Successivamente si affronta il problema dell'inseguimento di percorso. E' proposta una nuova struttura di controllo in grado di scalare in linea qualsiasi traiettoria pianificata, che potrebbe essere fisicamente irrealizzabile, in modo tale che i vincoli cinematici e dinamici che il sistema controllato impone siano soddisfatti. Infine si analizza il problema della generazione ottima di set-point per transizioni dello stato di generici sistemi nonlineari ed, in particolare, un innovativo metodo puramente differenziale per il controllo a tempo minimo è descritto

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein