Motion Planning of Uncertain Ordinary Differential Equation Systems

This work presents a novel motion planning framework, rooted in nonlinear programming theory, that treats uncertain fully and under-actuated dynamical systems described by ordinary differential equations. Uncertainty in multibody dynamical systems comes from various sources, such as: system parameters, initial conditions, sensor and actuator noise, and external forcing. Treatment of uncertainty in design is of paramount practical importance because all real-life systems are affected by it, and poor robustness and suboptimal performance result if it’s not accounted for in a given design. In this work uncertainties are modeled using Generalized Polynomial Chaos and are solved quantitatively using a least-square collocation method. The computational efficiency of this approach enables the inclusion of uncertainty statistics in the nonlinear programming optimization process. As such, the proposed framework allows the user to pose, and answer, new design questions related to uncertain dynamical systems. Specifically, the new framework is explained in the context of forward, inverse, and hybrid dynamics formulations. The forward dynamics formulation, applicable to both fully and under-actuated systems, prescribes deterministic actuator inputs which yield uncertain state trajectories. The inverse dynamics formulation is the dual to the forward dynamic, and is only applicable to fully-actuated systems; deterministic state trajectories are prescribed and yield uncertain actuator inputs. The inverse dynamics formulation is more computationally efficient as it requires only algebraic evaluations and completely avoids numerical integration. Finally, the hybrid dynamics formulation is applicable to under-actuated systems where it leverages the benefits of inverse dynamics for actuated joints and forward dynamics for unactuated joints; it prescribes actuated state and unactuated input trajectories which yield uncertain unactuated states and actuated inputs. The benefits of the ability to quantify uncertainty when planning the motion of multibody dynamic systems are illustrated through several case-studies. The resulting designs determine optimal motion plans—subject to deterministic and statistical constraints—for all possible systems within the probability space

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

DEVELOPMENT OF A SOFT PNEUMATIC ACTUATOR FOR MODULAR ROBOTIC MECHANISMS

Soft robotics is a widely and rapidly growing field of research today. Soft pneumatic actuators, as a fundamental element in soft robotics, have gained huge popularity and are being employed for the development of soft robots. During the last decade, a variety of hyper-elastic robotic systems have been realized. As the name suggests, such robots are made up of soft materials, and do not have any underlying rigid mechanical structure. These robots are actuated employing various methods like pneumatic, electroactive, jamming etc. Generally, in order to achieve a desired mechanical response to produce required actuation or manipulation, two or more materials having different stiffness are utilized to develop a soft robot. However, this method introduces complications in the fabrication process as well as in further design flexibility and modifications. The current work presents a design scheme of a soft robotic actuator adapting an easier fabrication approach, which is economical and environment friendly as well. The purpose is the realization of a soft pneumatic actuator having functional ability to produce effective actuation, and which is further employable to develop modular and scalable mechanisms. That infers to scrutinize the profile and orientation of the internal actuation cavity and the outer shape of viii the actuator. Utilization of a single material for this actuator has been considered to make this design scheme convenient. A commercial silicone rubber was selected which served for an economical process both in terms of the cost as well as its accommodating fabrication process through molding. In order to obtain the material behavior, \u2018Ansys Workbench 17.1 R \u2019 has been used. Cubic outline for the actuator aided towards the realization of a body shape which can easily be engaged for the development of modular mechanisms employing multiple units. This outer body shape further facilitates to achieve the stability and portability of the actuator. The soft actuator has been named \u2018Soft Cubic Module\u2019 based on its external cubic shape. For the internal actuation cavity design, various shapes, such as spherical, elliptical and cylindrical, were examined considering their different sizes and orientations within the cubic module. These internal cavities were simulated in order to achieve single degree of freedom actuation. That means, only one face of the cube is principally required to produce effective deformation. \u2018Creo Perametric 3.0 M 130\u2019 has been used to design the model and to evaluate the performance of actuation cavities in terms of effective deformation and the resulting von-mises stress. Out of the simulated profiles, cylindrical cavity with desired outcomes has been further considered to design the soft actuator. \u2018Ansys Workbench 17.1 R \u2019 environment was further used to assess the performance of cylindrical actuation cavity. Evaluation in two different simulation environments helped to validate the initially achieved results. The developed soft cubic actuator was then employed to develop different mechanisms in a single unit configuration as well as multi-unit robotic system developments. This design scheme is considered as the first tool to investigate its capacity to perform certain given tasks in various configurations. Alongside its application as a single unit gripper and a two unit bio-mimetic crawling mechanism, this soft actuator has been employed to realize a four degree ix of freedom robotic mechanism. The formation of this primitive soft robotic four axis mechanism is being further considered to develop an equivalent mechanism similar to the well known Stewart platform, with advantages of compactness, simpler kinematics design, easier control, and lesser cost. Overall, the accomplished results indicate that the design scheme of Soft Cubic Module is helpful in realizing a simple and cost-effective soft pneumatic actuator which is modular and scalable. Another favourable point of this scheme is the use of a single material with convenient fabrication and handling

Review of real brain-controlled wheelchairs

This paper presents a review of the state of the art regarding wheelchairs driven by a brain-computer interface (BCI). Using a brain-controlled wheelchair (BCW), disabled users could handle a wheelchair through their brain activity, granting autonomy to move through an experimental environment. A classification is established, based on the characteristics of the BCW, such as the type of electroencephalographic (EEG) signal used, the navigation system employed by the wheelchair, the task for the participants, or the metrics used to evaluate the performance. Furthermore, these factors are compared according to the type of signal used, in order to clarify the differences among them. Finally, the trend of current research in this field is discussed, as well as the challenges that should be solved in the future

Kineto-dynamic modeling of human upper limb for robotic manipulators and assistive applications

The sensory-motor architecture of human upper limb and hand is characterized by a complex inter-relation of multiple elements, such as ligaments, muscles, and joints. Nonetheless, humans are able to generate coordinated and meaningful motor actions to interact-and eventually explore-the external environment. Such a complexity reduction is usually studied within the framework of synergistic control, whose focus has been mostly limited on human grasping and manipulation. Little attention has been devoted to the spatio-temporal characterization of human upper limb kinematic strategies and how the purposeful exploitation of the environmental constraints shapes human execution of manipulative actions. In this chapter, we report results on the evidence of a synergistic control of human upper limb and during manipulation with the environment. We propose functional analysis to characterize main spatio-temporal coordinated patterns of arm joints. Furthermore, we study how the environment influences human grasping synergies. The effect of cutaneous impairment is also evaluated. Applications to the design and control of robotic and assistive devices are finally discussed

Scalability study for robotic hand platform

The goal of this thesis project was to determine the lower limit of scale for the RIT robotic grasping hand. This was accomplished using a combination of computer simulation and experimental studies. A force analysis was conducted to determine the size of air muscles required to achieve appropriate contact forces at a smaller scale. Input variables, such as the actuation force and tendon return force, were determined experimentally. A dynamic computer model of the hand system was then created using Recurdyn. This was used to predict the contact (grasping) force of the fingers at full-scale, half-scale, and quarter-scale. Correlation between the computer model and physical testing was achieved for both a life-size and half-scale finger assembly. To further demonstrate the scalability of the hand design, both half and quarter-scale robotic hand rapid prototype assemblies were built using 3D printing techniques. This thesis work identified the point where further miniaturization would require a change in the manufacturing process to micro-fabrication. Several techniques were compared as potential methods for making a production intent quarter-scale robotic hand. Investment casting, Swiss machining, and Selective Laser Sintering were the manufacturing techniques considered. A quarter-scale robotic hand tested the limits of each technology. Below this scale, micro-machining would be required. The break point for the current actuation method, air muscles, was also explored. Below the quarter-scale, an alternative actuation method would also be required. Electroactive Polymers were discussed as an option for the micro-scale. In summary, a dynamic model of the RIT robotic grasping hand was created and validated as scalable at full and half-scales. The model was then used to predict finger contact forces at the quarter-scale. The quarter-scale was identified as the break point in terms of the current RIT robotic grasping hand based on both manufacturing and actuation. A novel, prototype quarter-scale robotic hand assembly was successfully built by an additive manufacturing process, a high resolution 3D printer. However, further miniaturization would require alternate manufacturing techniques and actuation mechanisms

Kinematics and Robot Design IV, KaRD2021

This volume collects the papers published on the special issue “Kinematics and Robot Design IV, KaRD2021” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2021), which is the forth edition of the KaRD special-issue series, hosted by the open-access journal “MDPI Robotics”. KaRD series is an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2021, after the peer-review process, accepted 12 papers. The accepted papers cover some theoretical and many design/applicative aspects

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions