A two-wheeled machine with a handling mechanism in two different directions

Despite the fact that there are various configurations of self-balanced two-wheeled machines (TWMs), the workspace of such systems is restricted by their current configurations and designs. In this work, the dynamic analysis of a novel configuration of TWMs is introduced that enables handling a payload attached to the intermediate body (IB) in two mutually perpendicular directions. This configuration will enlarge the workspace of the vehicle and increase its flexibility in material handling, objects assembly and similar industrial and service robot applications. The proposed configuration gains advantages of the design of serial arms while occupying a minimum space which is unique feature of TWMs. The proposed machine has five degrees of freedoms (DOFs) that can be useful for industrial applications such as pick and place, material handling and packaging. This machine will provide an advantage over other TWMs in terms of the wider workspace and the increased flexibility in service and industrial applications. Furthermore, the proposed design will add additional challenge of controlling the system to compensate for the change of the location of the COM due to performing tasks of handling in multiple directions

Adaptive Sliding Mode Control of Mobile Manipulators with Markovian Switching Joints

The hybrid joints of manipulators can be switched to either active (actuated) or passive (underactuated) mode as needed. Consider the property of hybrid joints, the system switches stochastically between active and passive systems, and the dynamics of the jump system cannot stay on each trajectory errors region of subsystems forever; therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this paper, we consider stochastic stability and sliding mode control for mobile manipulators using stochastic jumps switching joints. Adaptive parameter techniques are adopted to cope with the effect of Markovian switching and nonlinear dynamics uncertainty and follow the desired trajectory for wheeled mobile manipulators. The resulting closed-loop system is bounded in probability and the effect due to the external disturbance on the tracking errors can be attenuated to any preassigned level. It has been shown that the adaptive control problem for the Markovian jump nonlinear systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. Finally, a numerical example is given to show the potential of the proposed techniques

Learning of Closed-Loop Motion Control

Learning motion control as a unified process of designing the reference trajectory and the controller is one of the most challenging problems in robotics. The complexity of the problem prevents most of the existing optimization algorithms from giving satisfactory results. While model-based algorithms like iterative linear-quadratic-Gaussian (iLQG) can be used to design a suitable controller for the motion control, their performance is strongly limited by the model accuracy. An inaccurate model may lead to degraded performance of the controller on the physical system. Although using machine learning approaches to learn the motion control on real systems have been proven to be effective, their performance depends on good initialization. To address these issues, this paper introduces a two-step algorithm which combines the proven performance of a model-based controller with a model-free method for compensating for model inaccuracy. The first step optimizes the problem using iLQG. Then, in the second step this controller is used to initialize the policy for our PI$^2$-01 reinforcement learning algorithm. This algorithm is a derivation of the PI$^2$ algorithm enabling more stable and faster convergence. The performance of this method is demonstrated both in simulation and experimental results

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Lab experiences for teaching undergraduate dynamics

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2003.Includes bibliographical references (p. 443-466).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.This thesis describes several projects developed to teach undergraduate dynamics and controls. The materials were developed primarily for the class 2.003 Modeling Dynamics and Control I. These include (1) a set of ActivLab modular experiments that illustrate the dynamics of linear time-invariant (LTI) systems and (2) a two wheeled mobile inverted pendulum. The ActivLab equipment has been designed as shareware, and plans for it are available on the web. The inverted pendulum robot developed here is largely inspired by the iBOT and Segway transportation devices invented by Dean Kamen.by Katherine A. Lilienkamp.S.M

Receding-horizon motion planning of quadrupedal robot locomotion

Quadrupedal robots are designed to offer efficient and robust mobility on uneven terrain. This thesis investigates combining numerical optimization and machine learning methods to achieve interpretable kinodynamic planning of natural and agile locomotion. The proposed algorithm, called Receding-Horizon Experience-Controlled Adaptive Legged Locomotion (RHECALL), uses nonlinear programming (NLP) with learned initialization to produce long-horizon, high-fidelity, terrain-aware, whole-body trajectories. RHECALL has been implemented and validated on the ANYbotics ANYmal B and C quadrupeds on complex terrain. The proposed optimal control problem formulation uses the single-rigid-body dynamics (SRBD) model and adopts a direct collocation transcription method which enables the discovery of aperiodic contact sequences. To generate reliable trajectories, we propose fast-to-compute analytical costs that leverage the discretization and terrain-dependent kinematic constraints. To extend the formulation to receding-horizon planning, we propose a segmentation approach with asynchronous centre of mass (COM) and end-effector timings and a heuristic initialization scheme which reuses the previous solution. We integrate real-time 2.5D perception data for online foothold selection. Additionally, we demonstrate that a learned stability criterion can be incorporated into the planning framework. To accelerate the convergence of the NLP solver to locally optimal solutions, we propose data-driven initialization schemes trained using supervised and unsupervised behaviour cloning. We demonstrate the computational advantage of the schemes and the ability to leverage latent space to reconstruct dynamic segments of plans which are several seconds long. Finally, in order to apply RHECALL to quadrupeds with significant leg inertias, we derive the more accurate lump leg single-rigid-body dynamics (LL-SRBD) and centroidal dynamics (CD) models and their first-order partial derivatives. To facilitate intuitive usage of costs, constraints and initializations, we parameterize these models by Euclidean-space variables. We show the models have the ability to shape rotational inertia of the robot which offers potential to further improve agility

Mathematical and Numerical Aspects of Dynamical System Analysis

From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”