In this thesis, I present two primary contributions towards more capable augmentative exoskeleton systems including (1) the design and implementation of a robot-agnostic, high-level control infrastructure for better real-time performance and (2) a cohesive framework for whole-body augmentative exoskeleton control in a high-degree-of-freedom (dof) exoskeleton system. Both contributions were part of a larger project, in which our team designed and built a form-fitting lower-body augmentative exoskeleton with the objective to enhance a pilot's load carrying ability without sacrificing speed or maneuverability. Modern high-level control systems require excellent timing and low communication latencies to ensure stable, robust, and high-performance multijoint control. Towards this end, I designed and implemented a nodelet-based high-level controller wrapper that abstracts away and optimizes many of the implementation details involved in building such a control infrastructure. My first iteration of improvements used ROS's (Robot Operating System) intraprocess communication protocol along with proper integration of our RT-preempt kernel to ensure reliable, low-jitter timing performance and low-latency communication. I then helped to design infrastructure improvements that further reduced round-trip times via full system synchronization. My high-level control infrastructure has enabled significant advances for a variety of projects in the Human-Centered Robotics Lab (HCRL), including the development of a controller for an augmentative exoskeleton and dynamic walking using the lab's point-foot bipedal robot, Mercury. The second major contribution in this thesis is an algorithm that I developed for whole-body augmentative exoskeleton control. It uses a model of the exoskeleton to cancel static, gravitational loads, and measured cuff forces to attenuate human-exo interaction forces, including inertial loads and those caused by disturbances from the environment. The key contribution of this control scheme relative to other exoskeleton transparency controllers is how this algorithm (1) handles contact switching given the corresponding discrete changes in the dynamics and (2) routes the needed reaction forces to the ground given the underactuated, floating-base dynamics with contact constraints. I formulate a Quadratic Programming (QP) optimization problem to solve for permissible reaction forces and actuator torques that come as close as possible to providing the desired dynamic attenuation behavior of the controller while also satisfying wrench-cone constraints for each of the exoskeleton's contacts. A relaxation variable, penalized in the cost function, ensures the solver can always find a feasible solution, and cost function weights penalizing contact point accelerations and reaction force magnitudes are smoothly interpolated to ensure continuous torque commands as the system switches between two discrete sets of contacts

Wearable Robotics: Systems and Applications provides a comprehensive overview of the entire field of wearable robotics, including active orthotics (exoskeleton) and active prosthetics for the upper and lower limb and full body. In its two major sections, wearable robotics systems are described from both engineering perspectives and their application in medicine and industry. Systems and applications at various levels of the development cycle are presented, including those that are still under active research and development, systems that are under preliminary or full clinical trials, and those in commercialized products. This book is a great resource for anyone working in this field, including researchers, industry professionals and those who want to use it as a teaching mechanism. Provides a comprehensive overview of the entire field, with both engineering and medical perspectives Helps readers quickly and efficiently design and develop wearable robotics for healthcare applications

The majority of powered lower-limb exoskeletons nowadays are designed to rigidly track time-based kinematic patterns, which forces users to follow specific joint positions. This kinematic control approach is limited to replicating the normative joint kinematics associated with one specific task and user at a time. These pre-defined trajectories cannot adjust to continuously varying activities or changes in user behavior associated with learning during gait rehabilitation. Time-based kinematic control approach must also recognize the user’s intent to transition from one task-specific controller to another, which is susceptible to errors in intent recognition and does not allow for a continuous range of activities. Moreover, fixed joint patterns also do not facilitate active learning during gait rehabilitation. People with partial or full volitional control of their lower extremities should be allowed to adjust their joint kinematics during the learning process based on corrections from the therapist. To address this issue, we propose that instead of tracking reference kinematic patterns, kinetic goals (for example, energy or force) can be enforced to provide a flexible learning environment and allow the user to choose their own kinematic patterns for different locomotor tasks. In this dissertation, we focus on an energetic control approach that shapes the Lagrangian of the human body and exoskeleton in closed loop. This energetic control approach, known as energy shaping, controls the system energy to a specific analytical function of the system state in order to induce different dynamics via the Euler-Lagrange equations. By explicitly modeling holonomic contact constraints in the dynamics, we transform the conventional Lagrangian dynamics into the equivalent constrained dynamics that have fewer (or possibly zero) unactuated coordinates. Based on these constrained dynamics, the matching conditions, which determine what energetic properties of the human body can be shaped, become easier to satisfy. By satisfying matching conditions for human-robot systems with arbitrary system dimension and degrees of actuation, we are therefore able to present a complete theoretical framework for underactuated energy shaping that incorporates both environmental and human interaction. Simulation results on a human-like biped model and experimental results with able-bodied subjects across a variety of locomotor tasks have demonstrated the potential clinical benefits of the proposed control approach.

This book aims at providing algorithms for balance control of legged, torque-controlled humanoid robots. A humanoid robot normally uses the feet for locomotion. This paradigm is extended by addressing the challenge of multi-contact balancing, which allows a humanoid robot to exploit an arbitrary number of contacts for support. Using multiple contacts increases the size of the support polygon, which in turn leads to an increased robustness of the stance and to an increased kinematic workspace of the robot. Both are important features for facilitating a transition of humanoid robots from research laboratories to real-world applications, where they are confronted with multiple challenging scenarios, such as climbing stairs and ladders, traversing debris, handling heavy loads, or working in confined spaces. The distribution of forces and torques among the multiple contacts is a challenging aspect of the problem, which arises from the closed kinematic chain given by the robot and its environment.

As robots designed for physical interaction with humans---humanoids, exoskeletons and beyond---make their entrance into society, understanding the limitations of their interaction behavior will be key to their effective use. The state of the art method for allowing such systems to be both compliant and force sensitive is to introduce mechanical springs into the joints of these robots, making them "series elastic". But this complicates the control of these robots, making it hard to separate truth from optimism in what they will be able to accomplish using feedback control. Robots are programmed in hierarchical layers, and each layer makes assumptions about the layer below it. The planning layer assumes the plan will be followed. The whole body controller layer assumes the actuators will supply whatever torque it specifies. And the actuator control layer assumes the actuator behaves like a linear system. This dissertation studies the interfaces between these layers as they are influenced by the choice to include series elastic actuation, hoping to resolve the mismatch between assumptions and guarantees that arise from this choice. These questions lead it naturally to the lowest of the layers, where a new system identification system allows the actuator to assume a bounded uncertainty model. The dissertation then refines the insights from studying uncertain SEA models into a simpler model that explains the most important factors. It uses this to design SEA controllers that go beyond the traditional limits of passivity. These insights also apply to the problem of strength augmentation exoskeleton control. Factor of 3 amplification results are reported on a tethered, 12 degree of freedom, powered, lower body exoskeleton with four passive joints using a simplified version of the controller and a far more advanced whole body control framework. These ideas are introduced in the context of the authors's work with various testbeds and state of the art robots including a point foot biped, the DARPA virtual robotics challenge simulator, the NASA R5 Valkyrie Humanoid, and the Apptronik Sagittarius Lower Body Exoskeleton

The new technological advances opened widely the application field of robots. Robots are moving from the classical application scenario with structured industrial environments and tedious repetitive tasks to new application environments that require more interaction with the humans. It is in this context that the concept of Wearable Robots (WRs) has emerged. One of the most exciting and challenging aspects in the design of biomechatronics wearable robots is that the human takes a place in the design, this fact imposes several restrictions and requirements in the design of this sort of devices. The key distinctive aspect in wearable robots is their intrinsic dual cognitive and physical interaction with humans. The key role of a robot in a physical human–robot interaction (pHRI) is the generation of supplementary forces to empower and overcome human physical limits. The crucial role of a cognitive human–robot interaction (cHRI) is to make the human aware of the possibilities of the robot while allowing them to maintain control of the robot at all times. This book gives a general overview of the robotics exoskeletons and introduces the reader to this robotic field. Moreover, it describes the development of an upper limb exoskeleton for tremor suppression in order to illustrate the influence of a specific application in the designs decisions.