Bioinspired template-based control of legged locomotion

cient and robust locomotion is a crucial condition for the more extensive use of legged robots in real world applications. In that respect, robots can learn from animals, if the principles underlying locomotion in biological legged systems can be transferred to their artificial counterparts. However, legged locomotion in biological systems is a complex and not fully understood problem. A great progress to simplify understanding locomotion dynamics and control was made by introducing simple models, coined ``templates'', able to represent the overall dynamics of animal (including human) gaits. One of the most recognized models is the spring-loaded inverted pendulum (SLIP) which consists of a point mass atop a massless spring. This model provides a good description of human gaits, such as walking, hopping and running. Despite its high level of abstraction, it supported and inspired the development of successful legged robots and was used as explicit targets for control, over the years. Inspired from template models explaining biological locomotory systems and Raibert's pioneering legged robots, locomotion can be realized by basic subfunctions: (i) stance leg function, (ii) leg swinging and (iii) balancing. Combinations of these three subfunctions can generate different gaits with diverse properties. Using the template models, we investigate how locomotor subfunctions contribute to stabilize different gaits (hopping, running and walking) in different conditions (e.g., speeds). We show that such basic analysis on human locomotion using conceptual models can result in developing new methods in design and control of legged systems like humanoid robots and assistive devices (exoskeletons, orthoses and prostheses). This thesis comprises research in different disciplines: biomechanics, robotics and control. These disciplines are required to do human experiments and data analysis, modeling of locomotory systems, and implementation on robots and an exoskeleton. We benefited from facilities and experiments performed in the Lauflabor locomotion laboratory. Modeling includes two categories: conceptual (template-based, e.g. SLIP) models and detailed models (with segmented legs, masses/inertias). Using the BioBiped series of robots (and the detailed BioBiped MBS models; MBS stands for Multi-Body-System), we have implemented newly-developed design and control methods related to the concept of locomotor subfunctions on either MBS models or on the robot directly. In addition, with involvement in BALANCE project (\url{http://balance-fp7.eu/}), we implemented balance-related control approaches on an exoskeleton to demonstrate their performance in human walking. The outcomes of this research includes developing new conceptual models of legged locomotion, analysis of human locomotion based on the newly developed models following the locomotor subfunction trilogy, developing methods to benefit from the models in design and control of robots and exoskeletons. The main contribution of this work is providing a novel approach for modular control of legged locomotion. With this approach we can identify the relation between different locomotor subfunctions e.g., between balance and stance (using stance force for tuning balance control) or balance and swing (two joint hip muscles can support the swing leg control relating it to the upper body posture) and implement the concept of modular control based on locomotor subfunctions with a limited exchange of sensory information on several hardware platforms (legged robots, exoskeleton)

Inverse Modeling of Human Knee Joint Based on Geometry and Vision Systems for Exoskeleton Applications

Current trends in Robotics aim to close the gap that separates technology and humans, bringing novel robotic devices in order to improve human performance. Although robotic exoskeletons represent a breakthrough in mobility enhancement, there are design challenges related to the forces exerted to the users’ joints that result in severe injuries. This occurs due to the fact that most of the current developments consider the joints as noninvariant rotational axes. This paper proposes the use of commercial vision systems in order to perform biomimetic joint design for robotic exoskeletons. This work proposes a kinematic model based on irregular shaped cams as the joint mechanism that emulates the bone-to-bone joints in the human body. The paper follows a geometric approach for determining the location of the instantaneous center of rotation in order to design the cam contours. Furthermore, the use of a commercial vision system is proposed as the main measurement tool due to its noninvasive feature and for allowing subjects under measurement to move freely. The application of this method resulted in relevant information about the displacements of the instantaneous center of rotation at the human knee joint

Application of wearable sensors in actuation and control of powered ankle exoskeletons: a Comprehensive Review

Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided

Ankle-Foot Orthosis Stiffness: Biomechanical Effects, Measurement and Emulation

Ankle-foot orthoses (AFOs) are braces worn by individuals with gait impairments to provide support about the ankle. AFOs come in a variety of designs for clinicians to choose from. However, as the effects of different design parameters on AFO properties and AFO users have not been adequately quantified, it is not clear which design choices are most likely to improve patient outcomes. Recent advances in manufacturing have further expanded the design space, adding urgency and complexity to the challenge of selecting optimal designs. A key AFO property affected by design decisions is sagittal-plane rotational stiffness. To evaluate the effectiveness of different AFO designs, we need: 1) a better understanding of the biomechanical effects of AFO stiffness and 2) more precise and repeatable stiffness measurement methods. This dissertation addresses these needs by accomplishing four aims. First, we conducted a systematic literature review on the influence of AFO stiffness on gait biomechanics. We found that ankle and knee kinematics are affected by increasing stiffness, with minimal effects on hip kinematics and kinetics. However, the lack of effective stiffness measurement techniques made it difficult to determine which specific values or ranges of stiffness influence biomechanics. Therefore, in Aim2, we developed an AFO stiffness measurement apparatus (SMApp). The SMApp is an automated device that non-destructively flexes an AFO to acquire operator- and trial-independent measurements of its torque-angle dynamics. The SMApp was designed to test a variety of AFO types and sizes across a wide range of flexion angles and speeds exceeding current alternatives. Common models of AFO torque-angle dynamics in literature have simplified the relationship to a linear fit whose slope represents stiffness. This linear approximation ignores damping parameters. However, as previous studies were unable to precisely control AFO flexion speed, the presence of speed effects has not been adequately investigated. Thus, in Aim3, we used the SMApp to test whether AFOs exhibit viscoelastic behaviors over the range of speeds typically achieved during walking. This study revealed small but statistically significant effects of flexion speed on AFO stiffness for samples of both traditional AFOs and novel 3-D printed AFOs, suggesting that more complex models that include damping parameters could be more suitable for modeling AFO dynamics. Finally, in Aim 4, we investigated the use of an active exoskeleton, that can haptically-emulate different AFOs, as a potential test bed for studying the effects of AFO parameters on human movement. Prior work has used emulation for rapid prototyping of candidate assistive devices. While emulators can mimic a physical device's torque-angle profile, the physical and emulated devices may have other differences that influence user biomechanics. Current studies have not investigated these differences, which limits translation of findings from emulated to physical devices. To evaluate the efficacy of AFO emulation as a research tool, we conducted a single-subject pilot study with a custom-built AFO emulator device. We compared user kinematics while walking with a physical AFO against those with an emulated AFO and found they elicited similar ankle trajectories. This dissertation resulted in the successful development and evaluation of a framework consisting of two test beds, one to assess AFO mechanical properties and another to assess the effects of these properties on the AFO user. These tools enable innovations in AFO design that can translate to measurable improvements in patient outcomes.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163219/1/deema_1.pd

Joint Trajectory Generation and High-level Control for Patient-tailored Robotic Gait Rehabilitation

This dissertation presents a group of novel methods for robot-based gait rehabilitation which were developed aiming to offer more individualized therapies based on the specific condition of each patient, as well as to improve the overall rehabilitation experience for both patient and therapist. A novel methodology for gait pattern generation is proposed, which offers estimated hip and knee joint trajectories corresponding to healthy walking, and allows the therapist to graphically adapt the reference trajectories in order to fit better the patient's needs and disabilities. Additionally, the motion controllers for the hip and knee joints, mobile platform, and pelvic mechanism of an over-ground gait rehabilitation robotic system are also presented, as well as some proposed methods for assist as needed therapy. Two robot-patient synchronization approaches are also included in this work, together with a novel algorithm for online hip trajectory adaptation developed to reduce obstructive forces applied to the patient during therapy with compliant robotic systems. Finally, a prototype graphical user interface for the therapist is also presented