743 research outputs found
Inertial Load Compensation by a Model Spinal Circuit During Single Joint Movement
Office of Naval Research (N00014-92-J-1309); CONACYT (Mexico) (63462
Nonlinear robust control of tendon–driven robot manipulators
This work addresses the position tracking control problem for tendon–driven robotic mechanisms in the presence of parametric uncertainty and additive external disturbances. Specifically, a full state feedback nonlinear robust controller is proposed to tackle the link position tracking problem for tendon–driven robot manipulators with uncertain dynamical system parameters. A robust backstepping approach has been utilized to achieve uniformly ultimately bounded tracking performance despite the lack of exact knowledge of the dynamical parameters and presence of additive but bounded disturbance terms. Stability of the overall system is proven via Lyapunov based arguments. Simulation studies performed on a two link planar robot manipulator driven by a six tendon mechanism are presented to illustrate the effectiveness and viability of the proposed approach.Scientific and Technological Research Council of Turkey (112E561
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A highly-underactuated robotic hand with force and joint angle sensors
This paper describes a novel underactuated robotic hand design. The hand is highly underactuated as it contains three fingers with three joints each controlled by a single motor. One of the fingers ("thumb") can also be rotated about the base of the hand, yielding a total of two controllable degrees-of-freedom. A key component of the design is the addition of position and tactile sensors which provide precise angle feedback and binary force feedback. Our mechanical design can be analyzed theoretically to predict contact forces as well as hand position given a particular object shape
Control for non-linear compliant actuation of an upper arm exoskeleton
Musculoskeletal diseases of the back and upper extremities are one of the main causes of sick leave in Europe. Exoskeletons are one possible approach to preventive measures. The Biomechatronics Group at Technische Universität Ilmenau is developing an antagonistically actuated exoskeleton with non-linear compliance to support flexion and extension of the elbow in repetitive tasks like in assembly. Here, we present a control strategy to achieve joint stiffness control while benefitting from the advantages of non-linear compliant actuation. We use a decentralized control approach, combining two PID controllers to control joint position and string force and thus, joint stiffness, in the antagonistically acting drive. We show limitations and benefits of this approach through simulation and measurement
Modeling and Control for a Class of Tendon-Driven Continuum Mechanisms
This thesis contributes to the emerging field of soft material robots and treats modeling, state estimation and control for a special class of continuum mechanisms.
The overall outcome of is a novel treatment of a continuum in robotics research. At first a description of the overall system as a tendon-driven multi-body system modeled by a nonlinear rigid-body dynamics is proposed. In combination with the introduced real-time pose and velocity estimation, nonlinear model-based control in real-time is possible. Furthermore, the structural properties of the model allow employing modern control methods for underactuated mechanical systems which are adapted to provide set point control for the upper platform.
The developed methods in modeling, state estimation and control presented in this work are experimentally validated on a humanoid robot.
Due to their promising results, this thesis lays the foundation for the use of tendon-driven continuum mechanisms as generic joint modules
for modular robotic systems which may mark the beginning of a new generation of light-weight robots
Design and Control of Compliant Actuation Topologies for Energy-Efficient Articulated Robots
Considerable advances have been made in the field of robotic actuation in recent
years. At the heart of this has been increased use of compliance. Arguably the most
common approach is that of Series-Elastic Actuation (SEA), and SEAs have evolved
to become the core component of many articulated robots. Another approach is
integration of compliance in parallel to the main actuation, referred to as Parallel-
Elastic Actuation (PEA). A wide variety of such systems has been proposed. While
both approaches have demonstrated significant potential benefits, a number of key
challenges remain with regards to the design and control of such actuators.
This thesis addresses some of the challenges that exist in design and control of compliant
actuation systems. First, it investigates the design, dynamics, and control of
SEAs as the core components of next-generation robots. We consider the influence of
selected physical stiffness on torque controllability and backdrivability, and propose
an optimality criterion for impedance rendering. Furthermore, we consider disturbance
observers for robust torque control. Simulation studies and experimental data
validate the analyses. Secondly, this work investigates augmentation of articulated
robots with adjustable parallel compliance and multi-articulated actuation for increased
energy efficiency. Particularly, design optimisation of parallel compliance
topologies with adjustable pretension is proposed, including multi-articulated arrangements.
Novel control strategies are developed for such systems. To validate the
proposed concepts, novel hardware is designed, simulation studies are performed,
and experimental data of two platforms are provided, that show the benefits over
state-of-the-art SEA-only based actuatio
On the intrinsic control properties of muscle and relexes: exploring the interaction between neural and musculoskeletal dynamics in the framework of the equilbrium-point hypothesis
The aim of this thesis is to examine the relationship between the intrinsic dynamics of the body and its neural control. Specifically, it investigates the influence of musculoskeletal properties on the control signals needed for simple goal-directed movements in the framework of the equilibriumpoint (EP) hypothesis. To this end, muscle models of varying complexity are studied in isolation and when coupled to feedback laws derived from the EP hypothesis. It is demonstrated that the dynamical landscape formed by non-linear musculoskeletal models features a stable attractor in joint space whose properties, such as position, stiffness and viscosity, can be controlled through differential- and co-activation of antagonistic muscles. The emergence of this attractor creates a new level of control that reduces the system’s degrees of freedom and thus constitutes a low-level motor synergy. It is described how the properties of this stable equilibrium, as well as transient movement dynamics, depend on the various modelling assumptions underlying the muscle model.
The EP hypothesis is then tested on a chosen musculoskeletal model by using an optimal feedback control approach: genetic algorithm optimisation is used to identify feedback gains that produce smooth single- and multijoint movements of varying amplitude and duration. The importance of different feedback components is studied for reproducing invariants observed in natural movement kinematics. The resulting controllers are demonstrated to cope with a plausible range of reflex delays, predict the use of velocity-error feedback for the fastest movements, and suggest that experimentally observed triphasic muscle bursts are an emergent feature rather than centrally
planned. Also, control schemes which allow for simultaneous control of movement duration and distance are identified.
Lastly, it is shown that the generic formulation of the EP hypothesis fails to account for the interaction torques arising in multijoint movements. Extensions are proposed which address this shortcoming while maintaining its two basic assumptions: control signals in positional rather than force-based frames of reference; and the primacy of control properties intrinsic to the body over internal models. It is concluded that the EP hypothesis cannot be rejected for single- or multijoint reaching movements based on claims that predicted movement kinematics are unrealistic
Advancements in Prosthetics and Joint Mechanisms
abstract: Robotic joints can be either powered or passive. This work will discuss the creation of a passive and a powered joint system as well as the combination system being both powered and passive along with its benefits. A novel approach of analysis and control of the combination system is presented.
A passive and a powered ankle joint system is developed and fit to the field of prosthetics, specifically ankle joint replacement for able bodied gait. The general 1 DOF robotic joint designs are examined and the results from testing are discussed. Achievements in this area include the able bodied gait like behavior of passive systems for slow walking speeds. For higher walking speeds the powered ankle system is capable of adding the necessary energy to propel the user forward and remain similar to able bodied gait, effectively replacing the calf muscle. While running has not fully been achieved through past powered ankle devices the full power necessary is reached in this work for running and sprinting while achieving 4x’s power amplification through the powered ankle mechanism.
A theoretical approach to robotic joints is then analyzed in order to combine the advantages of both passive and powered systems. Energy methods are shown to provide a correct behavioral analysis of any robotic joint system. Manipulation of the energy curves and mechanism coupler curves allows real time joint behavioral adjustment. Such a powered joint can be adjusted to passively achieve desired behavior for different speeds and environmental needs. The effects on joint moment and stiffness from adjusting one type of mechanism is presented.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201
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