Intelligent model-based control of complex three-link mechanisms

The aim of this study is to understand the complexity and control challenges of the locomotion of a three-link mechanism of a robot system. In order to do this a three-link robot gymnast (Robogymnast) has been built in Cardiff University. The Robogymnast is composed of three links (one arm, one torso, one leg) and is powered by two geared DC motors. Currently the robot has three potentiometers to measure the relative angles between adjacent links and only one tachometer to measure the relative angular position of the first link. A mathematical model for the robot is derived using Lagrange equations. Since the model is inherently nonlinear and multivariate, it presents more challenges when modelling the Robogymnast and dealing with control motion problems. The proposed approach for dealing with the design of the control system is based on a discrete-time linear model around the upright position of the Robogymnast. To study the swinging motion of the Robogymnast, a new technique is proposed to manipulate the frequency and the amplitude of the sinusoidal signals as a means of controlling the motors. Due to the many combinations of the frequency and amplitude, an optimisation method is required to find the optimal set. The Bees Algorithm (BA), a novel swarm-based optimisation technique, is used to enhance the performance of the swinging motion through optimisation of the manipulated parameters of the control actions. The time taken to reach the upright position at its best is 128 seconds. Two different control methods are adopted to study the balancing/stablising of the Robogymnast in both the downward and upright configurations. The first is the optimal control algorithm using the Linear Quadratic Regulator (LQR) technique with integrators to help achieve and maintain the set of reference trajectories. The second is a combination of Local Control (LC) and LQR. Each controller is implemented via reduced order state observer to estimate the unmeasured states in terms of their relative angular velocities. From the identified data in the relative angular positions of the upright balancing control, it is reported that the maximum amplitude of the deviation in the relative angles on average are approximately 7.5° for the first link and 18° for the second link. It is noted that the third link deviated approximately by 2.5° using only the LQR controller, and no significant deviation when using the LQR with LC. To explore the combination between swinging and balancing motions, a switching mechanism between swinging and balancing algorithm is proposed. This is achieved by dividing the controller into three stages. The first stage is the swinging control, the next stage is the transition control which is accomplished using the Independent Joint Control (IJC) technique and finally balancing control is achieved by the LQR. The duration time of the transition controller to track the reference trajectory of the Robogymnast at its best is found to be within 0.4 seconds. An external disturbance is applied to each link of the Robogymnast separately in order to study the controller's ability to overcome the disturbance and to study the controller response. The simulation of the Robogymnast and experimental realization of the controllers are implemented using MATLAB® software and the C++ program environment respectively

Current sensing feedback for humanoid stability

For humanoid robots to function in changing environments, they must be able to maintain balance similar to human beings. At present, humanoids recover from pushes by the use of either the ankles or hips and a rigid body. This method has been proven to work, but causes excessive strain on the joints of the robot and does not maximize on the capabilities of a humanlike body. The focus of this paper is to enable advanced dynamic balancing through torque classification and balance improving positional changes. For the robot to be able to balance dynamically, external torques must be determined accurately. The proposed method of this paper uses current sensing feedback at the humanoids power source to classify external torques. Through understanding the current draw of each joint, an external torque can be modeled. After being modeled, the external torque can be nullified with balancing techniques. Current sensing has the advantage that it adds detailed feedback while requiring small adjustments to the robot. Also, current sensing minimizes additional sensors, cost, and weight to the robot. Current sensing technology lies between the power supply and drive motors, thus can be implement without altering the robot. After an external torque has been modeled, the robot will undertake balancing positions to reduce the instability. The specialized positions increase the robot\u27s balance while reducing the workload of each joint. The balancing positions incorporate the humanlike body of the robot and torque from each of the leg servos. The best balancing positions were generated with a genetic algorithm and simulated in Webots. The simulation environment provided an accurate physical model and physics engine. The genetic algorithm reduced the workload of searching the workspace of a robot with ten degrees of freedom below the waist. The current sensing theory was experimentally tested on the TigerBot, a humanoid produced by the Rochester Institute of Technology (RIT). The TigerBot has twenty three degrees of freedom that fully simulate human motion. The robot stands at thirty-one inches tall and weighs close to nine pounds. The legs of the robot have six degrees of freedom per leg, which fully mimics the human leg. The robot was awarded first place in the 2012 IEEE design competition for innovation in New York

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Optimization-based control and planning for highly dynamic legged locomotion in complex environments

Legged animals can dynamically traverse unstructured environments in an elegant and efficient manner, whether it be running down a steep hill or leaping between branches. To harness part of the animal agility to the legged robot would unlock potential applications such as disaster response and planetary exploration. The unique challenge of these tasks is that the robot has to produce highly dynamic maneuvers in complex environments with minimum human guidance. This thesis explores how an optimization-based method can be applied in the control and planning of highly dynamic legged motions to address the locomotion problem in complex environments. Specifically, this work first describes the design synthesis of a small and agile quadrupedal robot \panther. Based on the quadruped platform, we developed a model predictive control (MPC) control framework to realize complex 3D acrobatic motions without resorting to switching among controllers. We present the MPC formulation that directly uses the rotation matrix, which avoids the singularity issue associated with Euler angles. Motion planning algorithms are developed for planar-legged robot traversing challenging terrains. Dynamic trajectories that simultaneously reason about contact, centroidal dynamics, and joint torque limit are obtained by solving mixed-integer convex programs (MICP) without requiring any initial guess from the operator. We further reduce the computational expense of long-horizon planning by leveraging the benefits of both optimization and sampling-based approaches for a simple legged robot. Finally, we present experimental results for each topic on legged robot hardware to validate the proposed method. It is our hope that the results presented in this thesis will eventually enable legged robots to achieve mobility autonomy at the level of biological systems

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Visual servo control on a humanoid robot

Includes bibliographical referencesThis thesis deals with the control of a humanoid robot based on visual servoing. It seeks to confer a degree of autonomy to the robot in the achievement of tasks such as reaching a desired position, tracking or/and grasping an object. The autonomy of humanoid robots is considered as crucial for the success of the numerous services that this kind of robots can render with their ability to associate dexterity and mobility in structured, unstructured or even hazardous environments. To achieve this objective, a humanoid robot is fully modeled and the control of its locomotion, conditioned by postural balance and gait stability, is studied. The presented approach is formulated to account for all the joints of the biped robot. As a way to conform the reference commands from visual servoing to the discrete locomotion mode of the robot, this study exploits a reactive omnidirectional walking pattern generator and a visual task Jacobian redefined with respect to a floating base on the humanoid robot, instead of the stance foot. The redundancy problem stemming from the high number of degrees of freedom coupled with the omnidirectional mobility of the robot is handled within the task priority framework, allowing thus to achieve con- figuration dependent sub-objectives such as improving the reachability, the manipulability and avoiding joint limits. Beyond a kinematic formulation of visual servoing, this thesis explores a dynamic visual approach and proposes two new visual servoing laws. Lyapunov theory is used first to prove the stability and convergence of the visual closed loop, then to derive a robust adaptive controller for the combined robot-vision dynamics, yielding thus an ultimate uniform bounded solution. Finally, all proposed schemes are validated in simulation and experimentally on the humanoid robot NAO

The Future of Humanoid Robots

This book provides state of the art scientific and engineering research findings and developments in the field of humanoid robotics and its applications. It is expected that humanoids will change the way we interact with machines, and will have the ability to blend perfectly into an environment already designed for humans. The book contains chapters that aim to discover the future abilities of humanoid robots by presenting a variety of integrated research in various scientific and engineering fields, such as locomotion, perception, adaptive behavior, human-robot interaction, neuroscience and machine learning. The book is designed to be accessible and practical, with an emphasis on useful information to those working in the fields of robotics, cognitive science, artificial intelligence, computational methods and other fields of science directly or indirectly related to the development and usage of future humanoid robots. The editor of the book has extensive R&D experience, patents, and publications in the area of humanoid robotics, and his experience is reflected in editing the content of the book

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area