A Robotic Torso Joint With Adjustable Linear Spring Mechanism for Natural Dynamic Motions in a Differential-Elastic Arrangement

To be operated in unknown or complex environments, modern robots have to fulfill various challenging criteria. Among them, one finds requirements such as a high level of robustness to withstand impacts and the capabilities to physically interact in a safe manner. One way to achieve that is to integrate variable-stiffness actuators into the systems, enabling compliant behavior through the elastic components and providing the additional adaptability of the impedance. Here, we introduce a novel adjustable linear stiffness joint mounted in a differential-elastic arrangement. The mechanism is integrated into the anthropomorphic upper body of the DLR David robot and responsible for the spinal rotation. Consequently, the actuator is crucial for the overall workspace of the robot and the realization of energy-efficient natural motions such as in dynamic running. The proposed hardware setup is experimentally validated in terms of the linearity in the spring characteristics, intrinsic damping, the excitation of resonance frequencies, and the ability to alter these resonance frequencies through stiffness adaptation during dynamic motions

An Overview on Principles for Energy Efficient Robot Locomotion

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied

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

Analysis of Actuator Control Strategies for Excitation of Intrinsic Modes in Compliant Robots with Series Elastic Actuators

In biology, body dynamics and elasticity in periodic motions most likely con- tribute to efficiency, i.e., in mammalian locomotion. Likewise, elastic elements can be added to robotic systems in an attempt to mimic this biological concept. Compliant robots are less likely to get damaged after severe impacts and their mechanical energy storage via springs could be exploited for fast and explosive movements. In this thesis, we explore the question whether resonance excitation that solely considers link-side dynamics or also takes into account the motor inertia, can lead to an increase in performance in Series Elastic Actuator (SEA) driven robotic systems. We propose three different control approaches and compare them to compliant state-of-the-art control as baseline evaluation in simulation and hardware experiments. Moreover, we extend the investigation of motor-side-excitation with the aid of methods such as inertia shaping and simulative system variation. Experiment results regarding a pick-and-place task with fixed amplitude reveal that in the investigated test setup, it might not be beneficial to make dedicated use of the motor inertia. Instead, an approach that exclusively excites link-side dynamics appears, for this particular task and setup, to be advantageous. However, generally, also making use of the motor dynamics bears potential for specific investigations as it appears more flexible and the control behavior can be easily adapted. Thus, the presented thesis provides first fundamental insights about novel control strategies and lies the foundation for further systematic research with different actuation types and varying task goals

Bio-inspired control concepts for elastic rotatory joint drives

Annunziata S. Bio-inspired control concepts for elastic rotatory joint drives. Bielefeld: Universität Bielefeld; 2014.Recent research in robotics focuses the attention on the control of compliant actuators to improve safety and to make the interaction with humans more natural. Lightweight construction, real elasticity directly integrated into the joint and control of joint compliance seem to play the most important role for improving safety in human-machine interaction. Humans are intrinsically elastic and the Central Nervous System (CNS) takes advantage of the nonlinear muscle properties to modulate joint stiffness through co-contraction of antagonistic muscles. If alterable compliance in robotic systems is desirable, its introduction can be achieved in two fundamentally different ways. The first way is a technical approach based on the idea of impedance control as formulated by Hogan (1985). The second approach is bioinspired and introduces physiological control mechanisms, muscle models and virtual antagonistic actuation into the control system of a robotics joint drive. Recently, biological models for the control of muscles in vertebrates have been developed (Franklin et al., 2008; Yang et al., 2011). Still, the question remains, how a control algorithm, acting on two or even more muscles, can be implemented in a technical joint. With the objective to implement bio-inspired control strategies on a robotic joint drive, in this thesis, musculoskeletal models, biological parameters and bio-inspired control laws are analyzed and tested. A simplified model of the human elbow joint is used to analyze muscle-like actuation and stiffness properties at the joint. Based on recent results related to how the CNS controls antagonistic muscles, a biological control pattern based on reciprocal activation and co-activation is tested for the control of torque and stiffness at the joint. However, a closer analysis of the musculoskeletal parameters reveals that, despite antagonistic co-activation, domains in the joint range of motion might occur for which stiffness variation is limited (low stiffness variability) or even impossible (stiffness nodes). The first part of this thesis presents novel strategies for simultaneous control of torque and stiffness in a hinge joint actuated by two antagonistic muscle pairs. One strategy handles stiffness nodes by shifting them away from the current joint position and thus regaining stiffness controllability. To prevent domains of low stiffness variation, an optimal biomechanical setup is sought and finally defined which allows for a maximal stiffness variation across a wide angular joint range. Based on this optimal setup, four additional control approaches are designed and tested in simulation which deliver stiffnesses and torques comparable to those obtained in the optimal case. The control approaches combine biologically justified aspects, like reciprocal activation and co-activation, with novel ideas like inverse dynamics model and activation overflow. The second part of the thesis focuses on the design, test and validation of a bio-inspired position and stiffness control strategy for a lightweight, intrinsically elastic, robotics joint drive. Reciprocal activation and co-activation are used here as a starting point to concurrently control stiffness and position (instead of torque). A stability analysis, performed on the human elbow joint model, confirms that the co-activation level (and, as a consequence, the stiffness level) affects the reaction of the joint to external perturbations in terms of oscillations and settling time. To account for the stability aspects and implement further mechanisms found in the CNS of vertebrates, models of the muscle spindles, Golgi tendon organs, alpha-motor neurons and Renshaw cells, are added to the control algorithm. Nevertheless, while in many biological systems, antagonistic muscles generate the movement of the joint, in simple robotic systems, the movement is generated by only one actuator. Therefore, in order to transmit the desired bio-inspired movement to the technical elbow, the sum of all muscle-torques acting on the joint (i.e. the net-torque at the joint), has to be transmitted to the lightweight, inherently elastic, joint drive and controlled. A speed-torque control cascade is designed, implemented and tested on the robotics joint drive. The impedance range of the human elbow joint is evaluated in simulation and compared to the range obtained when the technical joint drive is acting instead of its biological counterpart. The bio-inspired controlled joint drive is able to reach the desired position and modulate joint compliance according to the disturbance like humans do, both in static cases and during movements, while keeping stability

Bio-inspired robotic joint and manipulator : from biomechanical experimentation and modeling to human-like compliant finger design and control

textOne of the greatest challenges in controlling robotic hands is grasping and manipulating objects in unstructured and uncertain environments. Robotic hands are typically too rigid to react against unexpected impacts and disturbances in order to prevent damage. The human hands have great versatility and robustness due, in part, to the passive compliance and damping. Designing mechanical elements that are inspired by the nonlinear joint compliance of human hands is a promising solution to achieve human-like grasping and manipulation. However, the exact role of biomechanical elements in realizing joint stiffness is unknown. We conducted a series of experiments to investigate nonlinear stiffness and damping of the metacarpophalangeal (MCP) joint at the index finger. We designed a custom-made mechanism to integrate electromyography sensors (EMGs) and a motion capture system to collect data from 19 subjects. We investigated the relative contributions of muscle-tendon units and the MCP capsule ligament complex to joint stiffness with subject-specific modeling. The results show that the muscle-tendon units provide limited contribution to the passive joint compliance. This findings indicate that the parallel compliance, in the form of the capsule-ligament complex, is significant in defining the passive properties of the hand. To identify the passive damping, we used the hysteresis loops to investigate the energy dissipation function. We used symbolic regression and principal component analysis to derive and interpret the damping models. The results show that the nonlinear viscous damping depends on the cyclic frequency, and fluid and structural types of damping also exist at the MCP joint. Inspired by the nonlinear stiffness of the MCP joint, we developed a miniaturized mechanism that uses pouring liquid plastic to design energy storing elements. The key innovations in this design are: a) a set of nonlinear elasticity of compliant materials, b) variable pulley configurations to tune the stiffness profile, and c) pretension mechanism to scale the stiffness profile. The design exhibits human-like passive compliance. By taking advantage of miniaturized joint size and additive manufacturing, we incorporated the novel joint design in a novel robotic manipulator with six series elastic actuators (SEA). The robotic manipulator has passive joint compliance with the intrinsic property of human hands. To validate the system, we investigated the Cartesian stiffness of grasping with low-level force control. The results show that that the overall system performs a great force tracking with position feedback. The parallel compliance decreases the motor efforts and can stabilize the system.Mechanical Engineerin

Piezoelectric energy harvesting solutions

This paper reviews the state of the art in piezoelectric energy harvesting. It presents the basics of piezoelectricity and discusses materials choice. The work places emphasis on material operating modes and device configurations, from resonant to non-resonant devices and also to rotational solutions. The reviewed literature is compared based on power density and bandwidth. Lastly, the question of power conversion is addressed by reviewing various circuit solutions

Modelling and control of lightweight underwater vehicle-manipulator systems

This thesis studies the mathematical description and the low-level control structures for underwater robotic systems performing motion and interaction tasks. The main focus is on the study of lightweight underwater-vehicle manipulator systems. A description of the dynamic and hydrodynamic modelling of the underwater vehicle-manipulator system (UVMS) is presented and a study of the coupling effects between the vehicle and manipulator is given. Through simulation results it is shown that the vehicle’s capabilities are degraded by the motion of the manipulator, when it has a considerable mass with respect to the vehicle. Understanding the interaction effects between the two subsystems is beneficial in developing new control architectures that can improve the performance of the system. A control strategy is proposed for reducing the coupling effects between the two subsystems when motion tasks are required. The method is developed based on the mathematical model of the UVMS and the estimated interaction effects. Simulation results show the validity of the proposed control structure even in the presence of uncertainties in the dynamic model. The problem of autonomous interaction with the underwater environment is further addressed. The thesis proposes a parallel position/force control structure for lightweight underwater vehicle-manipulator systems. Two different strategies for integrating this control law on the vehicle-manipulator structure are proposed. The first strategy uses the parallel control law for the manipulator while a different control law, the Proportional Integral Limited control structure, is used for the vehicle. The second strategy treats the underwater vehicle-manipulator system as a single system and the parallel position/force law is used for the overall system. The low level parallel position/force control law is validated through practical experiments using the HDT-MK3-M electric manipulator. The Proportional Integral Limited control structure is tested using a 5 degrees-of-freedom underwater vehicle in a wave-tank facility. Furthermore, an adaptive tuning method based on interaction theory is proposed for adjusting the gains of the controller. The experimental results show that the method is advantageous as it decreases the complexity of the manual tuning otherwise required and reduces the energy consumption. The main objectives of this thesis are to understand and accurately represent the behaviour of an underwater vehiclemanipulator system, to evaluate this system when in contact with the environment and to design informed low-level control structures based on the observations made through the mathematical study of the system. The concepts presented in this thesis are not restricted to only vehicle-manipulator systems but can be applied to different other multibody robotic systems

Standing Posture Modeling and Control for a Humanoid Robot

Master'sMASTER OF ENGINEERIN

System Identification of Bipedal Locomotion in Robots and Humans

The ability to perform a healthy walking gait can be altered in numerous cases due to gait disorder related pathologies. The latter could lead to partial or complete mobility loss, which affects the patients’ quality of life. Wearable exoskeletons and active prosthetics have been considered as a key component to remedy this mobility loss. The control of such devices knows numerous challenges that are yet to be addressed. As opposed to fixed trajectories control, real-time adaptive reference generation control is likely to provide the wearer with more intent control over the powered device. We propose a novel gait pattern generator for the control of such devices, taking advantage of the inter-joint coordination in the human gait. Our proposed method puts the user in the control loop as it maps the motion of healthy limbs to that of the affected one. To design such control strategy, it is critical to understand the dynamics behind bipedal walking. We begin by studying the simple compass gait walker. We examine the well-known Virtual Constraints method of controlling bipedal robots in the image of the compass gait. In addition, we provide both the mechanical and control design of an affordable research platform for bipedal dynamic walking. We then extend the concept of virtual constraints to human locomotion, where we investigate the accuracy of predicting lower limb joints angular position and velocity from the motion of the other limbs. Data from nine healthy subjects performing specific locomotion tasks were collected and are made available online. A successful prediction of the hip, knee, and ankle joints was achieved in different scenarios. It was also found that the motion of the cane alone has sufficient information to help predict good trajectories for the lower limb in stairs ascent. Better estimates were obtained using additional information from arm joints. We also explored the prediction of knee and ankle trajectories from the motion of the hip joints