Optimal Mixed Tracking/Impedance Control With Application to Transfemoral Prostheses With Energy Regeneration

We design an optimal passivitybased tracking/impedance control system for a robotic manipulator with energy regenerative electronics, where the manipulator has both actively and semi-actively controlled joints. The semi-active joints are driven by a regenerative actuator that includes an energy-storing element. Method: External forces can have a large influence on energy regeneration characteristics. Impedance control is used to impose a desired relationship between external forces and deviation from reference trajectories. Multi-objective optimization (MOO) is used to obtain optimal impedance parameters and control gains to compromise between the two conflicting objectives of trajectory tracking and energy regeneration. We solve the MOO problem under two different scenarios: 1) constant impedance; and 2) timevarying impedance. Results: The methods are applied to a transfemoral prosthesis simulation with a semi-active knee joint. Normalized hypervolume and relative coverage are used to compare Pareto fronts, and these two metrics show that time-varying impedance provides better performance than constant impedance. The solution with time-varying impedance with minimum tracking error (0.0008 rad) fails to regenerate energy (loses 9.53 J), while a solution with degradation in tracking (0.0452 rad) regenerates energy (gains 270.3 J). A tradeoff solution results in fair tracking (0.0178 rad) and fair energy regeneration (131.2 J). Conclusion: Our experimental results support the possibility of net energy regeneration at the semi-active knee joint with human-like tracking performance. Significance: The results indicate that advanced control and optimization of ultracapacitor-based systems can significantly reduce power requirements in transfemoral prostheses

Design optimization and control of a parallel lower-arm exoskeleton

Wearable force feedback robotic devices, haptic exoskeletons, are becoming increasingly common as they find widespread use in medical and virtual reality (VR) applications. Allowing users to mechanically interact with computationally mediated environments, haptic exoskeletons provide users with better “immersion” to VR environments. Design of haptic exoskeletons is a challenging task, since in addition to being ergonomic and light weight, such devices are also required to satisfy the demands of any ideal force-feedback device: ability withstand human applied forces with very high stiffness and capacity to display a full range of impedances down to the minimum value human can perceive. If not properly designed by taking these conflicting requirements into account, the interface can significantly deteriorate the transparency of displayed forces; therefore, the choice of the kinematic structure and determination of the dimensions of this kinematic structure have significant impacts on the overall performance of any haptic display independent of the control algorithm employed. In this thesis, we first propose a general framework for optimal dimensional synthesis of haptic interfaces, in particular for haptic interfaces with closed kinematic chains, with respect to multiple design objectives. We identify and categorize the relevant performance criteria for the force feedback exoskeletons and address the trade-offs between them, by applying a Pareto-front based multi-objective design optimization procedure. Utilizing a fast converging gradient-based method, the proposed framework is computational efficient. Moreover, the approach is applicable to any set of performance indices and extendable to include any number of design criteria. Subsequently, we extend this framework to assist the selection of the most appropriate kinematic structure among multiple mechanisms. Specifically, we perform a rigorous comparison between two spherical parallel mechanisms (SPMs) that satisfy the ergonomic necessities of a human forearm and wrist and select the kinematic structure that results in superior performance for force-feedback applications. Utilizing the Pareto optimal set of solutions, we also assign dimensions to this mechanism to ensure an optimal trade-off between global kinematic and dynamic performance. Following the design optimization phase, we perform kinematic and dynamic analyses of the SPM-based exoskeleton in independent coordinates to facilitate efficient simulation and real-time implementation of model based controllers. We decide on the hardware components considering human wrist torque and force limits, safety and ergonomy constraints, and present the CAD model of a prototype of the exoskeleton. Finally, we implement model based task-space position and impedance controllers in simulation and present the results of them

A novel approach to micro-telemanipulation with soft slave robots: integrated design of a non-overshooting series elastic actuator

Micro mechanical devices are becoming ubiquitous as they find increas- ing uses in applications such as micro-fabrication, micro-surgery and micro- probing. Use of micro-electromechanical systems not only offer compactness and precision, but also increases the efficiency of processes. Whenever me- chanical devices are used to interact with the environment, accurate control of the forces arising at the interaction surfaces arise as an important chal- lenge. In this work, we propose using a series elastic actuation (SEA) for micro- manipulation. Since an SEA is an integrated mechatronic device, the me- chanical design and controller synthesis are handled in parallel to achieve the best overall performance. The mechanical design of the μSEA is handled in two steps: type selection and dimensional synthesis. In the type selection step, a compliant, half pantograph mechanism is chosen as the underlying kinematic structure of the coupling element. For optimal dimensioning, the bandwidth of the system, the disturbance response and the force resolution are considered to achieve good control performance with high reliability. These objectives are achieved by optimizing the manipulability and the stiffness of the mechanism along with a robustness constraint. In parallel with the mechanical design, a force controller is synthesized. The controller has a cascaded structure: an inner loop for position control and an outer loop for force control. Since excess force application can be detrimental during manipulation of fragile objects; the position controller of the inner loop is designed to be a non-overshooting controller which guar- antees the force response of the system always stay lower than the reference value. This self-standing μSEA system is embedded into a 3-channel scaled tele- operation architecture so that an operator can perform micro-telemanipulation. Constant scaling between the master and the slave is implemented and the teleoperator controllers preserve the non-overshooting nature of the μSEA. Finally, the designed μSEA based micro-telemanipulation system is im- plemented and characterized

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Design Optimization, Analysis, and Control of Walking Robots

Passive dynamic walking refers to the dynamical behavior of mechanical devices that are able to naturally walk down a shallow slope in a stable manner, without using actuation or sensing of any kind. Such devices can attain motions that are remarkably human-like by purely exploiting their natural dynamics. This suggests that passive dynamic walking machines can be used to model and study human locomotion; however, there are two major limitations: they can be difficult to design, and they cannot walk on level ground or uphill without some kind of actuation. This thesis presents a mechanism design optimization framework that allows the designer to find the best design parameters based on the chosen performance metric(s). The optimization is formulated as a convex problem, where its solutions are globally optimal and can be obtained efficiently. To enable locomotion on level ground and uphill, this thesis studies a robot based on a passive walker: the rimless wheel with an actuated torso. We design and validate two control policies for the robot through the use of scalable methodology based on tools from mathematical analysis, optimization theory, linear algebra, differential equations, and control theory

A Two-Stage Approach to Collaborative Fiber Placement through Coordination of Multiple Autonomous Industrial Robots

© 2018, Springer Nature B.V. The use of multiple Autonomous Industrial Robots (AIRs) as opposed to a single AIR to perform fiber placement brings about many challenges which have not been addressed by researchers. These challenges include optimal division and allocation of the work and performing path planning in a coordinated manner while considering the requirements and constraints that are unique to the fiber placement task. To solve these challenges, a two-stage approach is proposed in this paper. The first stage considers multiple objectives to optimally allocate each AIR with surface areas, while the second stage aims to generate coordinated paths for the AIRs. Within each stage, mathematical models are developed with several unique objectives and constraints that are specific to the multi-AIR collaborative fiber placement. Several case studies are presented to validate the approach and the proposed mathematical models. Comparison studies with different number of AIRs and variations of the developed mathematical models are also presented

Dynamics and control of robotic systems for on-orbit objects manipulation

Multi-body systems (MSs) are assemblies composed of multiple bodies (either rigid or structurally flexible) connected among each other by means of mechanical joints. In many engineering fields (such as aerospace, aeronautics, robotics, machinery, military weapons and bio-mechanics) a large number of systems (e.g. space robots, aircraft, terrestrial vehicles, industrial machinery, launching systems) can be included in this category. The dynamic characteristics and performance of such complex systems need to be accurately and rapidly analyzed and predicted. Taking this engineering background into consideration, a new branch of study, named as Multi-body Systems Dynamics (MSD), emerged in the 1960s and has become an important research and development area in modern mechanics; it mainly addresses the theoretical modeling, numerical analysis, design optimization and control for complex MSs. The research on dynamics modeling and numerical solving techniques for rigid multi-body systems has relatively matured and perfected through the developments over the past half century. However, for many engineering problems, the rigid multi-body system model cannot meet the requirements in terms of precision. It is then necessary to consider the coupling between the large rigid motions of the MS components and their elastic displacements; thus the study of the dynamics of flexible MSs has gained increasing relevance. The flexible MSD involves many theories and methods, such as continuum mechanics, computational mechanics and nonlinear dynamics, thus implying a higher requirement on the theoretical basis. Robotic on-orbit operations for servicing, repairing or de-orbiting existing satellites are among space mission concepts expected to have a relevant role in a close future. In particular, many studies have been focused on removing significant debris objects from their orbit. While mission designs involving tethers, nets, harpoons or glues are among options studied and analyzed by the scientific and industrial community, the debris removal by means of robotic manipulators seems to be the solution with the longest space experience. In fact, robotic manipulators are now a well-established technology in space applications as they are routinely used for handling and assembling large space modules and for reducing human extravehicular activities on the International Space Station. The operations are generally performed in a tele-operated approach, where the slow motion of the robotic manipulator is controlled by specialized operators on board of the space station or at the ground control center. Grasped objects are usually cooperative, meaning they are capable to re-orient themselves or have appropriate mechanisms for engagement with the end-effectors of the manipulator (i.e. its terminal parts). On the other hand, debris removal missions would target objects which are often non-controlled and lacking specific hooking points. Moreover, there would be a distinctive advantage in terms of cost and reliability to conduct this type of mission profile in a fully autonomous manner, as issues like obstacle avoidance could be more easily managed locally than from a far away control center. Space Manipulator Systems (SMSs) are satellites made of a base platform equipped with one or more robotic arms. A SMS is a floating system because its base is not fixed to the ground like in terrestrial manipulators; therefore, the motion of the robotic arms affects the attitude and position of the base platform and vice versa. This reciprocal influence is denoted as "dynamic coupling" and makes the dynamics modeling and motion planning of a space robot much more complicated than those of fixed-base manipulators. Indeed, SMSs are complex systems whose dynamics modeling requires appropriate theoretical and mathematical tools. The growing importance SMSs are acquiring is due to their operational ductility as they are able to perform complicated tasks such as repairing, refueling, re-orbiting spacecraft, assembling articulated space structures and cleaning up the increasing amount of space debris. SMSs have also been employed in several rendezvous and docking missions. They have also been the object of many studies which verified the possibility to extend the operational life of commercial and scientific satellites by using an automated servicing spacecraft dedicated to repair, refuel and/or manage their failures (e.g. DARPA's Orbital Express and JAXA's ETS VII). Furthermore, Active Debris Removal (ADR) via robotic systems is one of the main concerns governments and space agencies have been facing in the last years. As a result, the grasping and post-grasping operations on non-cooperative objects are still open research areas facing many technical challenges: the target object identification by means of passive or active optical techniques, the estimation of its kinematic state, the design of dexterous robotic manipulators and end-effectors, the multi-body dynamics analysis, the selection of approaching and grasping maneuvers and the post-grasping mission planning are the main open research challenges in this field. The missions involving the use of SMSs are usually characterized by the following typical phases: 1. Orbital approach; 2. Rendez-vous; 3. Robotic arm(s) deployment; 4. Pre-grasping; 5. Grasping and post-grasping operations. This thesis project will focus on the last three. The manuscript is structured as follows: Chapter 1 presents the derivation of a multi-body system dynamics equations further developing them to reach their Kane's formulation; Chapter 2 investigates two different approaches (Particle Swarm Optimization and Machine Learning) dealing with a space manipulator deployment maneuver; Chapter 3 addresses the design of a combined Impedance+PD controller capable of accomplishing the pre-grasping phase goals and Chapter 4 is dedicated to the dynamic modeling of the closed-loop kinematic chain formed by the manipulator and the grasped target object and to the synthesis of a Jacobian Transpose+PD controller for a post-grasping docking maneuver. Finally, the concluding remarks summarize the overall thesis contribution

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

A Generalized Method for Predictive Simulation-Based Lower Limb Prosthesis Design

Lower limb prostheses are designed to replace the functions and form of the missing biological anatomy. These functions are hypothesized to improve user outcome measures which are negatively affected by receiving an amputation – such as metabolic cost of transport, preferred walking speed, and perceived discomfort during walking. However, the effect of these design functions on the targeted outcome measures is highly variable, suggesting that these relationships are not fully understood. Biomechanics simulation and modeling tools are increasingly capable of analyzing the effects of a design on the resulting user gait. In this work, prothesis-aided gait is optimized in simulation to reduce both muscle effort and peak loads on the residual limb using a generalized prosthesis model. Compared to a traditional revolute powered ankle joint model, a two degree-of freedom generalized model reduced muscle activations by 50% and peak loads by 15%. Simulated prosthesis behaviors corresponding to the optimal gait patterns were translated into a two degree-of-freedom ankle-foot prosthesis design with powered bidirectional linear translation and plantarflexion. The prototype is capable of delivering up to 171 N-m of plantarflexion torque and 499 N of translation force, with 15° dorsi-/35° plantarflexion and 10 cm translation range of motion. The mass and height of the ankle-foot are 2.29 kg and 19.5 cm, respectively. The mass of the entire system including the wearable offboard system is 8.58 kg. This platform is designed to emulate the behavior of the simulated prosthesis, as well as be configurable to emulate alternate behaviors obtained from simulations with different optimization objectives. The prototype is controlled to replicate simulated walking patterns using a high level finite state controller, mid-level stiffness controller, and low level load controller. Closed loop load control has bandwidth of 15 Hz in translation and 7.2 Hz in flexion. Load tracking during walking with a single able-bodied human subject ranges from 93 to 159 N in translation and 4.6 to 21.3 N-m in flexion. The contribution of this work is to provide a framework for predictive simulation-based prosthesis design, evidence of its practical implementation, and the experimental tools to validate future predictive simulation studies