Dynamics and controls for robot manipulators with open and closed kinematic chain mechanisms

This dissertation deals with dynamics and controls for robot manipulators with open and closed kinematic chain mechanisms;Part I of this dissertation considers the problem of designing a class of robust algorithms for the trajectory tracking control of unconstrained single robot manipulator. The general control structure consists of two parts: The nominal control laws are first introduced to stabilize the system in the absence of uncertainties, then a class of robust nonlinear control laws are adopted to compensate for both the structured uncertainties and the unstructured uncertainties by using deterministic approach. The possible upper bounds of uncertainties are assumed to be known for the nonadaptive version of robust nonlinear controls. If information on these bounds is not available, then the adaptive bound of the robust controller is presented to overcome possible time-varying uncertainties (i.e., decentralized adaptive control scheme);Part II of the dissertation presents the efficient methodology of formulating system dynamics and hybrid position/force control for a single robot manipulator under geometric end-effector constraints. In order to facilitate dynamic analysis and control synthesis, the original joint-space dynamics (or a set of DAEs) is transformed into the constraint-space model through nonlinear transformations. Using the transformed dynamic model, a class of hybrid control laws are presented to manipulate the position and contact force at the end-effector simultaneously and accurately: the modified computed torque method, the robust adaptive controller, and the adaptive hybrid impedance controller;Part III of the dissertation deals with a mathematical modeling and coordinated control of multiple robot manipulators holding and transporting a rigid common object on the constraint surfaces. First, the kinematics and dynamics of multiple robot systems containing the closed-chain mechanisms are formulated from a unified viewpoint. After a series of model transformations, a new combined dynamic model is derived for dynamic analysis and control synthesis. Next, a class of hybrid position/force controllers are developed. The control laws can be used to simultaneously control the position of the object along the constraint surfaces and the contact forces (the internal grasping forces and the external constraint forces)

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation

A generic computer simulation for manipulator systems (ROBSIM) was implemented and the specific technologies necessary to increase the role of automation in various missions were developed. The specific items developed are: (1) capability for definition of a manipulator system consisting of multiple arms, load objects, and an environment; (2) capability for kinematic analysis, requirements analysis, and response simulation of manipulator motion; (3) postprocessing options such as graphic replay of simulated motion and manipulator parameter plotting; (4) investigation and simulation of various control methods including manual force/torque and active compliances control; (5) evaluation and implementation of three obstacle avoidance methods; (6) video simulation and edge detection; and (7) software simulation validation

Multi-rotor Aerial Vehicles in Physical Interactions: A Survey

Research on Multi-rotor Aerial Vehicles (MAVs) has experienced remarkable advancements over the past two decades, propelling the field forward at an accelerated pace. Through the implementation of motion control and the integration of specialized mechanisms, researchers have unlocked the potential of MAVs to perform a wide range of tasks in diverse scenarios. Notably, the literature has highlighted the distinctive attributes of MAVs that endow them with a competitive edge in physical interaction when compared to other robotic systems. In this survey, we present a categorization of the various types of physical interactions in which MAVs are involved, supported by comprehensive case studies. We examine the approaches employed by researchers to address different challenges using MAVs and their applications, including the development of different types of controllers to handle uncertainties inherent in these interactions. By conducting a thorough analysis of the strengths and limitations associated with different methodologies, as well as engaging in discussions about potential enhancements, this survey aims to illuminate the path for future research focusing on MAVs with high actuation capabilities

Adaptive Passivity-based Hybrid Pose/Force Control for Uncertain Robots

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