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Review Article

Appl. Mech. Rev. 2018;70(1):010801-010801-9. doi:10.1115/1.4038795.

Flying insects are able to navigate complex and highly dynamic environments, can rapidly change their flight speeds and directions, are robust to environmental disturbances, and are capable of long migratory flights. However, flying robots at similar scales have not yet demonstrated these characteristics autonomously. Recent advances in mesoscale manufacturing, novel actuation, control, and custom integrated circuit (IC) design have enabled the design of insect-scale flapping wing micro air vehicles (MAVs). However, there remain numerous constraints to component technologies—for example, scalable high-energy density power storage—that limit their functionality. This paper highlights the recent developments in the design of small-scale flapping wing MAVs, specifically discussing the various power and actuation technologies selected at various vehicle scales as well as the control architecture and avionics onboard the vehicle. We also outline the challenges associated with creating an integrated insect-scale flapping wing MAV.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):010802-010802-15. doi:10.1115/1.4038931.

This paper presents a review of the literature related to the use of redundancy in parallel mechanisms. Two types of redundancies are considered, namely, actuation redundancy and kinematic redundancy. The use of these concepts in the literature is highlighted. Each of the concepts is then formulated mathematically in order to clearly expose their characteristics and their properties. Two subclasses of kinematically redundant parallel mechanisms are defined, namely, those with serial redundant legs and those with parallel redundant legs. The force transmission in redundant parallel mechanisms is then discussed. Finally, a summary of the different approaches that can be used to implement redundancy in parallel mechanisms is given in order to identify the most promising synthesis avenues and to provide insight into their potential fields of application.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):010803-010803-18. doi:10.1115/1.4039078.

We provide a tutorial and review of the state-of-the-art in robot dynamics algorithms that rely on methods from differential geometry, particularly the theory of Lie groups. After reviewing the underlying Lie group structure of the rigid-body motions and the geometric formulation of the equations of motion for a single rigid body, we show how classical screw-theoretic concepts can be expressed in a reference frame-invariant way using Lie-theoretic concepts and derive recursive algorithms for the forward and inverse dynamics and their differentiation. These algorithms are extended to robots subject to closed-loop and other constraints, joints driven by variable stiffness actuators, and also to the modeling of contact between rigid bodies. We conclude with a demonstration of how the geometric formulations and algorithms can be effectively used for robot motion optimization.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):010804-010804-19. doi:10.1115/1.4039145.

As robotic devices are applied to problems beyond traditional manufacturing and industrial settings, we find that interaction between robots and humans, especially physical interaction, has become a fast developing field. Consider the application of robotics in healthcare, where we find telerobotic devices in the operating room facilitating dexterous surgical procedures, exoskeletons in the rehabilitation domain as walking aids and upper-limb movement assist devices, and even robotic limbs that are physically integrated with amputees who seek to restore their independence and mobility. In each of these scenarios, the physical coupling between human and robot, often termed physical human robot interaction (pHRI), facilitates new human performance capabilities and creates an opportunity to explore the sharing of task execution and control between humans and robots. In this review, we provide a unifying view of human and robot sharing task execution in scenarios where collaboration and cooperation between the two entities are necessary, and where the physical coupling of human and robot is a vital aspect. We define three key themes that emerge in these shared control scenarios, namely, intent detection, arbitration, and feedback. First, we explore methods for how the coupled pHRI system can detect what the human is trying to do, and how the physical coupling itself can be leveraged to detect intent. Second, once the human intent is known, we explore techniques for sharing and modulating control of the coupled system between robot and human operator. Finally, we survey methods for informing the human operator of the state of the coupled system, or the characteristics of the environment with which the pHRI system is interacting. At the conclusion of the survey, we present two case studies that exemplify shared control in pHRI systems, and specifically highlight the approaches used for the three key themes of intent detection, arbitration, and feedback for applications of upper limb robotic rehabilitation and haptic feedback from a robotic prosthesis for the upper limb.

Commentary by Dr. Valentin Fuster

Discussion

Appl. Mech. Rev. 2018;70(1):015501-015501-2. doi:10.1115/1.4038796.

Flying insects exhibit truly remarkable capabilities. There has been significant interest in developing small-scale flying robots by taking inspiration from flying insects. The paper by Helbling and Wood reports remarkable progress made by the research community in realizing insect-scale flapping wing vehicles and identifies research challenges and opportunities. This discussion builds upon their paper and examines the potential of insect-scale flapping wing flight from an application point of view. It summarizes requirements and mention implications of these requirements on propulsion, power, and control architecture.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):015502-015502-5. doi:10.1115/1.4039080.

Lie-theoretic methods provide an elegant way to formulate many problems in robotics, and the tutorial by Park et al. (2018, “Geometric Algorithms for Robot Dynamics: A Tutorial Review,” ASME Appl. Mech. Rev., 70(1), p. 010803) is simultaneously a complete and concise introduction to these methods as they pertain to robot dynamics. The central reason why Lie groups are a natural mathematical tool for robotics is that rigid-body motions and pose changes can be described as Lie groups, and allow phenomena including robot kinematics and dynamics to be formulated in elegant notation without introducing superfluous coordinates. The emphasis of the tutorial by Park et al. (2018, “Geometric Algorithms for Robot Dynamics: A Tutorial Review,” ASME Appl. Mech. Rev., 70(1), p. 010803) is robot dynamics from a Lie-theoretic point of view. Newton–Euler and Lagrangian formulation of robot dynamics algorithms with O(n) complexity were formulated more than 35 years ago using recurrence relations that use the serial structure of manipulator arms. This was done without using the knowledge of Lie theory. But issues such as why the ω× terms in rigid-body dynamics appear can be more easily understood in the context of this theory. The authors take great efforts to be understandable by nonexperts and present extensive references to the differential-geometric and Lie-group-centric formulations of manipulator dynamics. In the discussion presented here, connections are made to complementary methods that have been developed in other bodies of literature. This includes the multibody dynamics, geometric mechanics, spacecraft dynamics, and polymer physics literature, as well as robotics works that present non-Lie-theoretic formulations in the context of highly parallelizable algorithms.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):015503-015503-3. doi:10.1115/1.4039146.

A unifying description of the shared control architecture within the field of physical human–robot interaction (pHRI) facilitates the education of those being introduced to the field and the framing of new contributions to it. The authors' review of shared control within pHRI proposes such a unifying framework composed of three pillars. First, intent detection addresses the robot's interpretation of human goals, representing one-way communication. Second, arbitration manages the respective roles of the human and robot in the shared control. Third, feedback is the mechanism by which the robot returns information to the human, representing one-way communication in the opposite direction. Interpreting existing contributions through the lens of this framework brings out the importance of mechanical design, modeling, and state-based control.

Commentary by Dr. Valentin Fuster

Closure

Appl. Mech. Rev. 2018;70(1):016001-016001-1. doi:10.1115/1.4038797.

The authors of the review article “A Review of Propulsion, Power, and Control Architectures for Insect-Scale Flapping wing Vehicles” [1] greatly appreciated the commentary by Dr. S. K. Gupta [2]. We believe that he has identified numerous practical considerations that were not covered in depth in our review and that nicely complement our review such that, in aggregate, the two present a complete picture of the challenges and opportunities for developing and deploying autonomous insect-like vehicles. In particular, Dr. Gupta highlights the need for payload and flight time that are adequate for a desired mission or scenario. This brings up an inherent conundrum in the design of any flying vehicle (i.e., greater mission duration requires more onboard energy storage, leading to more massive storage device and a commensurate increase in required thrust to compensate, also increasing energy consumption; thus, increasing mission duration while keeping vehicle size constant is a significant challenge). Radical new solutions for energy harvesting or quantum breakthroughs in energy storage technologies are needed to get away from this tradeoff. Similarly, communication poses a challenge since even low-power wireless communication can consume a comparable amount of power as required for flight (Bluetooth Low Energy, for example, can consume more than 100 mW of power while transmitting, and we measured the power for flight of the RoboBee in Ref. [3] to be 19 mW2). This motivates exploration into communication strategies that leverage either semipassive communication methods, such as explored for MEMS sensor mote applications [4], or as Gupta points out, multifunctional use of components otherwise needed for the flight and control apparatus.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):016002-016002-1. doi:10.1115/1.4039079.

We are grateful to Chirikjian for his in-depth analysis and insightful comments [1] on our tutorial review [2], which complement nicely our main discussion on how Lie group methods can be effectively used for robot dynamics. There is considerable machinery from the theory of Lie groups and differential geometry that impact robot dynamics, and more generally nonlinear mechanics, and Chirikjian's commentary offers a deeper but still very much readable discussion of Lie group essentials that our review paper did not cover. Chirikjian also provides important context to our review by further pointing out the past literature on robot dynamics that is not based on Lie group methods, e.g., recursive methods for inverse and forward dynamics based on classical Denavit–Hartenberg kinematic representations. Finally, the discussion and additional references pointed out by Chirikjian on Lie group methods for modeling constrained multibody systems, and connections with variational integrators and discrete Lagrangian mechanics, provide fitting closure to our review, by pointing the reader to the latest developments and trends in geometric methods for robot and multibody system dynamics. Hopefully having made the case that there are both important analytical and computational benefits to using Lie group methods for multibody dynamics, we would remark that there is still quite a ways to go in this program to “geometrize” classical mechanics, and plenty of new application domains and open problems.

Commentary by Dr. Valentin Fuster
Appl. Mech. Rev. 2018;70(1):016004-016004-2. doi:10.1115/1.4039225.

In their discussion article [1] on our review paper [2], Professors James Schmiedeler and Patrick Wensing have provided an insightful and informative perspective of the roles of intent detection, arbitration, and communication as three pillars of a framework for the implementation of shared control in physical human–robot interaction (pHRI). The authors both have significant expertise and experience in robotics, bipedal walking, and robotic rehabilitation. Their commentary introduces commonalities between the themes of the review paper and issues in locomotion with the aid of an exoskeleton or lower-limb prostheses, and presents several important topics that warrant further exploration. These include mechanical design as it pertains to the physical coupling between human and robot, modeling the human to improve intent detection and the arbitration of control, and finite-state machines as an approach for implementation. In this closure, we provide additional thoughts and discussion of these topics as they relate to pHRI.

Commentary by Dr. Valentin Fuster

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