The power dissipation method and kinematic reducibility of multiple-model robotic systems

This paper develops a formal connection between the power dissipation method (PDM) and Lagrangian mechanics, with specific application to robotic systems. Such a connection is necessary for understanding how some of the successes in motion planning and stabilization for smooth kinematic robotic systems can be extended to systems with frictional interactions and overconstrained systems. We establish this connection using the idea of a multiple-model system, and then show that multiple-model systems arise naturally in a number of instances, including those arising in cases traditionally addressed using the PDM. We then give necessary and sufficient conditions for a dynamic multiple-model system to be reducible to a kinematic multiple-model system. We use this result to show that solutions to the PDM are actually kinematic reductions of solutions to the Euler-Lagrange equations. We are particularly motivated by mechanical systems undergoing multiple intermittent frictional contacts, such as distributed manipulators, overconstrained wheeled vehicles, and objects that are manipulated by grasping or pushing. Examples illustrate how these results can provide insight into the analysis and control of physical systems

Symmetries in Motion: Geometric Foundations of Motion Control

Some interesting aspects of motion and control, such as those found in biological and robotic locomotion and attitude control of spacecraft, involve geometric concepts. When an animal or a robot moves its joints in a periodic fashion, it can rotate or move forward. This observation leads to the general idea that when one variable in a system moves in a periodic fashion, motion of the Whole object can result. This property can be used for control purposes; the position and attitude Of a satellite, for example, are often controlled by periodic motions of parts of the satellite, such as spinning rotors. One of the geometric tools that has been used to describe this phenomenon is that of connections, a notion that is used extensively in general relativity and other parts of theoretical physics. This tool, part of the general subject Of geometric mechanics, has been helpful in the study of both the stability and instability of a system and system bifurcations, that is, changes in the nature of the system dynamics, as some parameter changes. Geometric mechanics, currently in a period of rapid evolution, has been used, for example, to design stabilizing feedback control systems in attitude dynamics. Theory is also being developed for systems with rolling constraints such as those found in a simple rolling wheel. This paper explains how some of these tools of geometric mechanics are used in the study of motion control and locomotion generation

Robust navigation control and headland turning optimization of agricultural vehicles

Autonomous agricultural robots have experienced rapid development during the last decade. They are capable of automating numerous field operations such as data collection, spraying, weeding, and harvesting. Because of the increasing demand of field work load and the diminishing labor force on the contrary, it is expected that more and more autonomous agricultural robots will be utilized in future farming systems. The development of a four-wheel-steering (4WS) and four-wheel-driving (4WD) robotic vehicle, AgRover, was carried out at Agricultural Automation and Robotics Lab at Iowa State University. As a 4WS/4WD robotic vehicle, AgRover was able to work under four steering modes, including crabbing, front steering, rear steering, and coordinated steering. These steering modes provided extraordinary flexibilities to cope with off-road path tracking and turning situations. AgRover could be manually controlled by a remote joystick to perform activities under individual PID controller of each motor. Socket based software, written in Visual C#, was developed at both AgRover side and remote PC side to manage bi-directional data communication. Safety redundancy was also considered and implemented during the software development. One of the prominent challenges in automated navigation control for off-road vehicles is to overcome the inaccuracy of vehicle modeling and the complexity of soil-tire interactions. Further, the robotic vehicle is a multiple-input and multiple-output (MIMO) high-dimensional nonlinear system, which is hard to be controlled or incorporated by conventional linearization methods. To this end, a robust nonlinear navigation controller was developed based on the Sliding Mode Control (SMC) theory and AgRover was used as the test platform to validate the controller performance. Based on the theoretical framework of such robust controller development, a series of field experiments on robust trajectory tracking control were carried out and promising results were achieved. Another vitally important component in automated agricultural field equipment navigation is automatic headland turning. Until now automated headland turning still remains as a challenging task for most auto-steer agricultural vehicles. This is particularly true after planting where precise alignment between crop row and tractor or tractor-implement is critical when equipment entering the next path. Given the motion constraints originated from nonholonomic agricultural vehicles and allowable headland turning space, to realize automated headland turning, an optimized headland turning trajectory planner is highly desirable. In this dissertation research, an optimization scheme was developed to incorporate vehicle system models, a minimum turning-time objective, and a set of associated motion constraints through a direct collocation nonlinear programming (DCNLP) optimization approach. The optimization algorithms were implemented using Matlab scripts and TOMLAB/SNOPT tool boxes. Various case studies including tractor and tractor-trailer combinations under different headland constraints were conducted. To validate the soundness of the developed optimization algorithm, the planner generated turning trajectory was compared with the hand-calculated trajectory when analytical approach was possible. The overall trajectory planning results clearly demonstrated the great potential of utilizing DCNLP methods for headland turning trajectory optimization for a tractor with or without towed implements

Single wheel robot: gyroscopical stabilization on ground and on incline.

by Loi-Wah Sun.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 77-81).Abstracts in English and Chinese.Abstract --- p.iAcknowledgments --- p.iiiContents --- p.vList of Figures --- p.viiList of Tables --- p.viiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.1.1 --- Literature review --- p.2Chapter 1.1.2 --- Gyroscopic precession --- p.5Chapter 1.2 --- Thesis overview --- p.7Chapter 2 --- Dynamics of the robot on ground --- p.9Chapter 2.1 --- System model re-derivation --- p.10Chapter 2.1.1 --- Linearized model --- p.15Chapter 2.2 --- A state feedback control --- p.16Chapter 2.3 --- Dynamic characteristics of the system --- p.18Chapter 2.4 --- Simulation study --- p.19Chapter 2.4.1 --- The self-stabilizing dynamics effect of the single wheel robot --- p.21Chapter 2.4.2 --- The Tilting effect of flywheel on the robot --- p.23Chapter 2.5 --- Dynamic parameters analysis --- p.25Chapter 2.5.1 --- Swinging pendulum --- p.25Chapter 2.5.2 --- Analysis of radius ratios --- p.27Chapter 2.5.3 --- Analysis of mass ratios --- p.30Chapter 3 --- Dynamics of the robot on incline --- p.33Chapter 3.1 --- Modeling of rolling disk on incline --- p.33Chapter 3.1.1 --- Disk rolls up on an inclined plane --- p.37Chapter 3.2 --- Modeling of single wheel robot on incline --- p.39Chapter 3.2.1 --- Kinematic constraints --- p.40Chapter 3.2.2 --- Equations of motion --- p.41Chapter 3.2.3 --- Model simplification --- p.43Chapter 3.2.4 --- Linearized model --- p.46Chapter 4 --- Control of the robot on incline --- p.47Chapter 4.1 --- A state feedback control --- p.47Chapter 4.1.1 --- Simulation study --- p.49Chapter 4.2 --- Backstepping-based control --- p.51Chapter 4.2.1 --- Simulation study --- p.53Chapter 4.2.2 --- The effect of the spinning rate of flywheel --- p.56Chapter 4.2.3 --- Simulation study --- p.58Chapter 4.2.4 --- Roll up case --- p.58Chapter 4.2.5 --- Roll down case --- p.58Chapter 5 --- Motion planning --- p.61Chapter 5.1 --- Performance index --- p.61Chapter 5.2 --- Condition of rolling up --- p.62Chapter 5.3 --- Motion planning of rolling Up --- p.65Chapter 5.3.1 --- Method I : Orientation change --- p.65Chapter 5.3.2 --- Method II : Change the initial velocities --- p.69Chapter 5.4 --- Wheel rolls Down --- p.70Chapter 5.4.1 --- Terminal velocity of rolling body down --- p.73Chapter 6 --- Summary --- p.75Chapter 6.1 --- Contributions --- p.75Chapter 6.2 --- Future Works --- p.76Bibliography --- p.7

Sliding mode control applied in trajectory-tracking of WMRs and autonomous vehicles

Tese de doutoramento apresentada à Fac. de Ciências e Tecnologia da Universidade de CoimbraThe thesis is structured as follows: • Chapter 2: Trajectory tracking problems are summarized. • Chapter 3: Kinematic and dynamic modeling of theWMRs and car-like robots are presented. • Chapter 4: The concept of sliding mode are first introduced. Then the fundamentals of SMC are summarized, including basic definitions, methods of sliding surface and control law design, robustness properties and the methods on handling chattering problems. New sliding-mode trajectory-tracking and slidingmode path-following controllers for WMRs and car-like vehicles, are also proposed in this chapter. • Chapter 5: The trajectory/path planning are developed, including the velocity profile. • Chapter 6: A model with two freedom degrees is considered for the HNC model. The user comfort is examined not only in the time domain, but also in the frequency domain. • Chapter 7: Experimental results obtained with the implementation of the proposed controllers in RobChair are summarized and discussed. • Chapter 8: Finally, conclusions are drawn and some suggestions for future work are provided

Adaptive Optimal Dynamic Control for Nonholonomic Systems

In this paper two different control methods are combined for controlling a typical nonholonomic device (a bicycle) the dynamic model and parameters of which are only approximately known. Most of such devices suffer from the problem that the time-derivatives of the coordinates of their location and orientation cannot independently be set so an arbitrarily prescribed trajectory cannot precisely be traced by them. For tackling this difficulty Optimal Control is proposed that can find acceptable compromise between the tracking error of the various coordinates. Further problem is that the solution proposed by the optimal controller cannot exactly be implemented in the lack of precise information on the dynamic model of the system. Based on the decoupled nature of the dynamic model of the longitudinal and lateral behavior of the engine special fixed point transformations are proposed to achieve adaptive tracking. These transformations were formerly successfully applied for the control of holonomic systems. It is the first time that the combined method is checked for various trajectories and dynamic model errors via simulation. It yielded promising results

Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations

This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications

Control structure for a car-like robot using artificial neural networks and genetic algorithms

The idea of improving human’s life quality by making life more comfortable and easy is nowadays possible using current technologies and techniques to solve complex daily problems. The presented idea in this work proposes a control strategy for autonomous robotic systems, specifically car-like robots. The main objective of this work is the development of a reactive navigation controller by means of obstacles avoidance and position control to reach a desired position in an unknown environment. This research goal was achieved by the integration of potential fields and neuroevolution controllers. The neuro-evolutionary controller was designed using the (NEAT) algorithm “Neuroevolution of Augmented Topologies” and trained using a designed training environment. The methodology used allowed the vehicle to reach a certain level of autonomy, obtaining a stable controller that includes kinematic and dynamic considerations. The obtained results showed significant improvements compared to the comparison workCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQNão te

Steering for a Class of Dynamic Nonholonomic Systems

In this paper we derive control algorithms for a class of dynamic nonholonomic steering problems, characterized as mechanical systems with nonholonomic constraints and symmetries. Recent research in geometric mechanics has led to a single, simplified framework that describes this class of systems, which includes examples such as wheeled mobile robots; undulatory robotic and biological locomotion systems, such as paramecia, inchworms, and snakes; and the reorientation of satellites and underwater vehicles. This geometric framework has also been applied to more unusual examples, such as the snakeboard robot, bicycles, the wobblestone, and the reorientation of a falling cat. We use this geometric framework as a basis for developing two types of control algorithms for such systems. The first is geared towards local controllability, using a perturbation approach to establish results similar to steering using sinusoids. The second method utilizes these results in applying more traditional steering algorithms for mobile robots, and is directed towards generating more non-local control methods of steering for this class of systems