DOCSLIB.ORG

On the Control of Complementary-Slackness Juggling Mechanical Systems Bernard Brogliato, Arturo Zavala Rio

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
On the Control of Complementary-Slackness Juggling Mechanical Systems Bernard Brogliato, Arturo Zavala Rio On the control of complementary-slackness juggling mechanical systems Bernard Brogliato, Arturo Zavala Rio To cite this version: Bernard Brogliato, Arturo Zavala Rio. On the control of complementary-slackness juggling mechanical systems. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2000, 45 (2), pp.235-246. 10.1109/9.839946. hal-02303804 HAL Id: hal-02303804 https://hal.archives-ouvertes.fr/hal-02303804 Submitted on 2 Oct 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. On the Control of Complementary-Slackness Juggling Mechanical Systems Bernard Brogliato and Arturo Zavala Río Abstract—This paper studies the feedback control of a class (2) of complementary-slackness hybrid mechanical systems. Roughly, (3) the systems we study are composed of an uncontrollable part (the “object”) and a controlled one (the “robot”), linked by a unilateral where the classical dynamics of Lagrangian systems is in (1), constraint and an impact rule. A systematic and general control de- sign method for this class of systems is proposed. The approach is the set of unilateral constraints is in (2) with , a nontrivial extension of the one degree-of-freedom (DOF) juggler and the so-called complementarity conditions [14] are in (3), control design. In addition to the robot control, it is also useful to where is the Lagrange multiplier vector. We assume study some intermediate controllability properties of the object’s frictionless constraints. , , impact Poincaré mapping, which generally takes the form of a non- , , and are the generalized coordinate linear discrete-time system. The force input mainly consists of a family of dead-beat feedback control laws, introduced via a recur- vector, the inertia matrix, the Coriolis and centrifugal terms, the sive procedure, and exploiting the underlying discrete-time struc- gravity forces and torques, and the control input, respectively, ture of the system. The main goal of this paper is to highlight the and . In order to render the dynamical system com- role of various physical and control properties characteristic of the plete, we must add to (1)–(3) a so-called restitution law that re- system on its stabilizability properties and to propose solutions in lates postimpact and preimpact velocities. Such physical rules certain cases. are necessary [30], [40]. The most widely used restitution rule Index Terms—Complementary slackness, feedback, hybrid, im- is known as Newton’s conjecture [4]. It is based on the knowl- pact Poincaré mappings, nonsmooth, underactuated, viabililty. edge of restitution coefficients . When ,itis represented in its generalized form as follows: I. INTRODUCTION (4) A. General Introduction where , , and generically denote ECENT researches in the robotics and the systems and the impact times (the superindices and stand, respectively, R control communities on mechanical systems subject to for the instants just after and just before the collisions), with unilateral constraints have focused on stabilization of manipu- . In case of a codimension 1 con- lators during complete robotic tasks [10], [39], well-posedness straint ( ), from energetical arguments. The and system theoretic issues [9], [30]–[32], walking and hopping system in (1)–(4) is complete, in the sense that, given preimpact machines [1], [5], [7], [8], [12], control of juggling and catching velocities , we are able to calculate the postimpact veloci- robots [6], [26], [27], [33], [37], systems with dynamic backlash ties and continue the integration after the collision has occurred. [2], [16], stabilization of polyhedral objects in some manipula- Notice that the system in (1)–(4) is a complex hybrid dynamical tion tasks [35], and nonprehensile manipulation [11], [19], [24]; system [32]. This class of dynamical systems can be divided fur- see [19] for a more complete bibliography on this last topic. ther into subclasses. In particular, the case in which the free-mo- The work presented in this paper focuses essentially on the last tion dynamics are controllable has recently received attention five listed topics. The open-loop models used are basically rigid [31], [39]. This class does not, however, cover some impacting body dynamics with a set of unilateral constraints on the gener- robotic systems. Indeed, write the dynamical equations of a two alized position. Such hybrid dynamical systems may be repre- degree-of-freedom (DOF) juggler; i.e., a system composed of sented as follows: an object (a point mass) subject to gravity, which rebounds on a (1) controlled table, as shown in Fig. 1: (5) (6) (7) B. Brogliato is with the Laboratoire d’Automatique de Grenoble (UMR 5528 (8) CNRS-INPG), ENSIEG, BP 46, 38402 St. Martin d’Hères, France (e-mail: [email protected]). A. Zavala Río was with the Mechanical Engineering Laboratory (MITI), Tsukuba, Ibaraki 305-8564, Japan. He is now with the University de Queretaro, Facultad de Ingenieria, DEPFI, 76010 Queretaro, Qro., Mexico (e-mail: (9) [email protected]). Restitution rule in (4) (10) Fig. 1. One and two DOF jugglers. Notice that the ball dynamics in (5) and (6) are not controlled like the impact damper [2], [16], we may consider that (11) cre- because only gravity acts on the ball. Hence, the only way to ates disturbances in the dynamics of (12), or on the contrary, we influence the trajectory of the ball is through impacts. This is may desire to control (11) using the impacts. In this paper, we a strong motivation for considering the feedback control of a will mainly focus on the control of from the input in (12), two DOF juggler, as in (5)–(10), because it represents a sim- via sequences of impacts. In other words, we shall restrict our- plified model of manipulation of objects through “controlled” selves to control tasks with zero-measure contact phases. The collisions with a robotic device [35]. We may suppose that the controllability and stabilizability properties of such hybrid sys- length of the surface is infinite. Hence, the impacts always occur tems, which depend on the vector fields in (11) and (12) and on with the same side of the table. In this paper, we shall use this in (13), have not yet been fully understood. It is advocated here example as an illustration of the influence of the physical and that impact Poincaré mappings [40] provide a suitable frame- control parameters on the control design. work for such analysis. Let us introduce the following defini- tion. B. A Class of Complementary-Slackness Hybrid Systems Definition 1: A viable controller is a function Juggling robots may also be considered as a particular case such that 1) or and of a class of complementary-slackness systems between programmed impact times, and 2) and are right-continuous of local bounded (11) variation (LBV) in time. (12) Here, programmed impacts are defined as those shock in- (13) stants planned in the control design (contrary to accidental im- pacts that may be caused by various model uncertainties or dis- where , , ( and turbances in the control loop). As we shall see, the sequence may have the same or different values), and a restitution rule depends on the controller design that in turn must in- has to be added to complete the model. Notice that if , corporate the object ballistic constraints. Let us recall that an such a system may a priori evolve in different modes [32]: LBV function possesses a countable set of discontinuity points its hybridness is therefore intrinsic. As indicated in the title and [21]; hence, a viable input ensures the well-posedness of the the abstract, we choose to generically name such systems jug- closed-loop system. glers, even though, as we shall see later, other types of sys- Definition 2: The “object” in (11) is controllable if given tems may fall into this class. In this setting, (11) plays the role , , satisfying the object’s ballistic constraints, of the “object,” and (12) is the “robot.” may repre- and , such that , and , a viable sent the “distance” between the object and the robot, but this is control law that drives from to exists, with not always the case, as some examples will prove. A necessary . condition to transform (1) into (11) and (12) is that a general- The study of such notions, however, requires some interme- ized coordinate transformation exists and ful- diate steps, for which some basic properties are important (in- fills for all , terestingly enough, some of them are similar to those done in . Also consider , and notice that the [17] for the control of a class of cascaded nonlinear systems system in (11) and (12) corresponds to (1) written in a non- that model some nonholonomic mechanical systems). Among controllable canonical form. Such systems are therefore quite those: different from so-called triangular systems [15]. In particular, 1) the properties of the object’s flow setting , (11) and (12) are not in general locally feedback on [explicit knowledge of the trajecto- stabilizable because the uncontrollable modes are not nec- ries, or controllability with state and input ]; essarily stable. The control problem for (11)–(13) may change 2) the controllability of (12); depending on our goal: for instance, in a system with clearance, 3) the controllability of (11) through impacts; 4) the relative degree1 of with respect to and the capsulate the whole essence of the general problem. It provides relative degrees of with respect to ; us, however, with a nice starting point.
Load more

Recommended publications
  • Quadrocopter Ball Juggling
    Quadrocopter Ball Juggling Mark Muller,¨ Sergei Lupashin and Raffaello D’Andrea Abstract— This paper presents a method allowing a quadro- dancing [8]; balancing an inverted pendulum [9]; aggressive copter with a rigidly attached racket to hit a ball towards a manoeuvres such as flight through windows and perching target. An algorithm is developed to generate an open loop [10]; and cooperative load-carrying [11]. trajectory guiding the vehicle to a predicted impact point – the prediction is done by integrating forward the current position The problem of hitting a ball also yields opportunities and velocity estimates from a Kalman filter. By examining for exploring learning and adaptation: presented here are the ball and vehicle trajectories before and after impact, strategies to identify the drag properties of the ball, the the system estimates the ball’s drag coefficient, the racket’s racket’s coefficient of restitution, and a strategy to compen- coefficient of restitution and an aiming bias. These estimates sate for aiming errors, allowing the system to improve its are then fed back into the system’s aiming algorithm to improve future performance. The algorithms are implemented for three performance over time. This provides a significant boost in different experiments: a single quadrocopter returning balls performance, but only represents an initial step at system- thrown by a human; two quadrocopters co-operatively juggling wide learning. We believe that this system, and systems like a ball back-and-forth; and a single quadrocopter attempting to it, provide strong motivation to experiment with automatic juggle a ball on its own. Performance is demonstrated in the learning in semi-constrained, dynamic environments.
    [Show full text]
  • Robust Hybrid Control Systems
    UNIVERSITY of CALIFORNIA Santa Barbara Robust Hybrid Control Systems A Dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical and Computer Engineering by Ricardo G. Sanfelice Committee in charge: Professor Andrew R. Teel, Chair Professor Petar V. Kokotovi´c Professor Jo˜ao P. Hespanha Professor Bassam Bamieh September 2007 Robust Hybrid Control Systems Copyright c 20071 by Ricardo G. Sanfelice 1Revised on January 2008. To my mother Alicia, and my father Adolfo iii Acknowledgements I am deeply grateful to my advisor, mentor, and friend Andy Teel for having guided me through the challenges of academic life and for teaching me to strive for elegance and mathematical rigor in my research. He has continuously motivated me to think creatively and to always aim for high-quality research. I would like to express my gratitude to my family and friends who have given me constant emotional and spiritual support and encouragement throughout my doctorate program. In particular, I want to thank my wife Christine who has been bold and remained supportive even in the busiest times of this journey. I also want to thank the faculty in the Department of Electrical and Computer Engineering and in the Center of Control, Dynamics, and Computation who directly or indirectly have shaped my career. In particular, I want to thank Petar Kokotovi`cand Jo˜ao Hespanha for their encouragement, advice, and friendship throughout the years. I thank all of the members of my doctoral committee for insightful discussions and useful suggestions made to improve this document. I am grateful to my fellow graduate students, post-docs, and visitors who made graduate school an enjoyable experience and were always available for discussions.
    [Show full text]
  • Sequential Composition of Dynamically Dexterous Robot Behaviors
    R. R. Burridge Sequential Texas Robotics and Automation Center Metrica, Inc. Composition Houston, Texas 77058, USA [email protected] of Dynamically A. A. Rizzi Dexterous Robot The Robotics Institute Carnegie Mellon University Behaviors Pittsburgh, Pennsylvania 15213-3891, USA [email protected] D. E. Koditschek Artificial Intelligence Laboratory and Controls Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor, Michigan 48109-2110, USA [email protected] Abstract we want to explore the control issues that arise from dynamical interactions between robot and environment, such as active We report on our efforts to develop a sequential robot controller- balancing, hopping, throwing, catching, and juggling. At the composition technique in the context of dexterous “batting” maneu- same time, we wish to explore how such dexterous behaviors vers. A robot with a flat paddle is required to strike repeatedly at can be marshaled toward goals whose achievement requires a thrown ball until the ball is brought to rest on the paddle at a at least the rudiments of strategy. specified location. The robot’s reachable workspace is blocked by In this paper, we explore empirically a simple but for- an obstacle that disconnects the free space formed when the ball and mal approach to the sequential composition of robot behav- paddle remain in contact, forcing the machine to “let go” for a time iors. We cast “behaviors” —robotic implementations of user- to bring the ball to the desired state. The controller compositions specified tasks—in a form amenable to representation as state we create guarantee that a ball introduced in the “safe workspace” regulation via feedback to a specified goal set in the pres- remains there and is ultimately brought to the goal.
    [Show full text]
  • On the Control of a One Degree-Of-Freedom Juggling Robot Bernard Brogliato, Arturo Zavala-Río
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Archive Ouverte en Sciences de l'Information et de la Communication On the Control of a One Degree-of-Freedom Juggling Robot Bernard Brogliato, Arturo Zavala-Río To cite this version: Bernard Brogliato, Arturo Zavala-Río. On the Control of a One Degree-of-Freedom Juggling Robot. Dynamics and Control, Springer Verlag, 1999, 9 (1), pp.67-91. 10.1023/A:1008346825330. hal- 02303974 HAL Id: hal-02303974 https://hal.archives-ouvertes.fr/hal-02303974 Submitted on 2 Oct 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. On the Control of a One Degree-of-Freedom Juggling Robot A . Z AVA L A - R IO´ [email protected] Laboratoire d’Automatique de Grenoble (UMR 5528 CNRS-INPG), ENSIEG, BP 46, 38402 St. Martin d’Heres,` France B. BROGLIATO [email protected] Laboratoire d’Automatique de Grenoble (UMR 5528 CNRS-INPG), ENSIEG, BP 46, 38402 St. Martin d’Heres,` France Abstract. This paper is devoted to the feedback control of a one degree-of-freedom (dof) juggling robot, considered as a subclass of mechanical systems subject to a unilateral constraint.
    [Show full text]
  • Reinforcement Learning: a Survey
    Journal of Articial Intelligence Research Submitted published Reinforcement Learning A Survey Leslie Pack Kaelbling lpkcsbrownedu Michael L Littman mlittmancsbrownedu Computer ScienceDepartment Box Brown University Providence RI USA Andrew W Mo ore awmcscmuedu Smith Hal l Carnegie Mel lon University Forbes Avenue Pittsburgh PA USA Abstract This pap er surveys the eld of reinforcement learning from a computerscience p er sp ective It is written to b e accessible to researchers familiar with machine learning Both the historical basis of the eld and a broad selection of currentwork are summarized Reinforcement learning is the problem faced by an agent that learns b ehavior through trialanderror interactions with a dynamic environment The work describ ed here has a resemblance to work in psychology but diers considerably in the details and in the use of the word reinforcement The pap er discusses central issues of reinforcement learning including trading o exploration and exploitation establishing the foundations of the eld via Markov decision theory learning from delayed reinforcement constructing empirical mo dels to accelerate learning making use of generalization and hierarchy and coping with hidden state It concludes with a survey of some implemented systems and an assessment of the practical utility of current metho ds for reinforcement learning Intro duction Reinforcement learning dates back to the early days of cyb ernetics and work in statistics psychology neuroscience and computer science In the last vetotenyears it has
    [Show full text]
  • Englisch Title
    High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards Jonglage mit einem Highspeed-Roboterarm Master thesis by Kai Ploeger Date of submission: May 28, 2020 1. Review: M.Sc. Michael Lutter 2. Review: Prof. Dr. Jan Peters Darmstadt Erklärung zur Abschlussarbeit gemäß §22 Abs. 7 und §23 Abs. 7 APB der TU Darmstadt Hiermit versichere ich, Kai Ploeger, die vorliegende Masterarbeit ohne Hilfe Dritter und nur mit den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die Quellen entnommen wurden, sind als solche kenntlich gemacht worden. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbehörde vorgelegen. Mir ist bekannt, dass im Fall eines Plagiats (§38 Abs. 2 APB) ein Täuschungsversuch vorliegt, der dazu führt, dass die Arbeit mit 5,0 bewertet und damit ein Prüfungsversuch verbraucht wird. Abschlussarbeiten dürfen nur einmal wiederholt werden. Bei der abgegebenen Thesis stimmen die schriftliche und die zur Archivierung eingereichte elektronische Fassung gemäß §23 Abs. 7 APB überein. Bei einer Thesis des Fachbereichs Architektur entspricht die eingereichte elektronische Fassung dem vorgestellten Modell und den vorgelegten Plänen. Darmstadt, 28. Mai 2020 Kai Ploeger Abstract Robots that can learn in the physical world will be important to enable robots to overcome their stiff and pre-programmed movements. For dynamic high-acceleration tasks, such as juggling, learning in the real-world is particularly challenging as one must push the limits of the robot and its actuation without harming the system. Therefore, learning these tasks on physical system amplifies the necessity of sample efficiency and safety for robot learning algorithms, making a high-speed task an ideal benchmark to highlight robot learning systems.
    [Show full text]
  • Mathematics in Jugglingjuggling in Mathematics
    History Siteswap notation of juggling Juggling braids Mathematics in Juggling Juggling in Mathematics Michal Zamboj Faculty of Mathematics and Physics × Faculty of Education Charles University The Jarní doktorandská škola didaktiky matematiky 19. - 21. 5. 2017 Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids The first historical evidence of juggling in the Beni Hassan location in Egypt, between 1994-1781 B.C.. Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids The first historical evidence of juggling in the Beni Hassan location in Egypt, between 1994-1781 B.C.. Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids • Why? ... describe juggling • How? ... describe juggling Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids Why? JUGGLER MATHEMATICIAN - "language" - notation - new tricks - new properties - understanding principles - application to related theo- ries Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids Claude Elwood Shannon, 1916-2001 • Construction of a juggling robot (1970s) • Underlying mathematical concept - Uniform juggling Michal Zamboj Mathematics in Juggling / Juggling in Mathematics History Siteswap notation of juggling Juggling braids Claude Elwood Shannon, 1916-2001 • h hands, b balls d
    [Show full text]
  • I JUST AROUND the CORNER
    JUST AROUND THE CORNER: AND SOME OTHER STORIES ____________________ A University Thesis Presented to the Faculty of California State University, East Bay ____________________ In Partial Fulfillment of the Requirements for the Degree Master of Arts in English ____________________ By Fordy (Stanford) M. Shoor II December 2018 i JUST AROUND THE CORNER: AND SOME OTHER STORJES By Fordy (Stanford) M. Shoor II Approved: Date: I I 'if j 1.--/ i / ~D j $; t I ii TABLE OF CONTENTS Acknowledgments iv Day Camp 1 Wall-to-Wall Carpeting 29 The Five Ball Cascade 33 Save the Bay! 59 Good on Paper 80 Checkout Counter 97 Just Around the Corner 124 Manicured 172 A Last Minute Trip 193 Pile-Up 199 iii ACKNOWLEDGEMENTS The author would like to acknowledge for the development of these stories professors Stephen Gutierrez, Jaqueline Doyle, Susan Gubernat, Douglas Taylor, Georgina Kleege, Leigh Burrill, Melanie Abrams, Eric Pape, John Campion, Kirsten Tranter and Benjamin Hale. Colleagues Ali-Jones Bey, Natasha Von Kaenel, Brendan Nystedt, Marisa Gomez, Katrina Wedding, Institutions Sarah Lawrence College, West Valley College, University of California Berkeley and California State University East Bay Literature and Writing Workshops. The Summer Creative Writing Program at UC Berkeley, Atom and Arroyo Magazines. Family Brittany Fajardo, Stan Shoor and Laurie Duckham Shoor iv 1 Day Camp More than any game, the campers prefer “Murderer”. To play it, they need to be lined up along the fence or handball court, as counselors choose a secret murderer and a public detective. The murderer will never reveal himself to the detective. They’re at a party, circling each other, shaking hands in brief introduction before moving on to the next stranger, often meeting the same person in repetition until the game is over.
    [Show full text]
  • Robot Arm Control Exploiting Natural Dynamics Matthew M. Williamson
    Robot Arm Control Exploiting Natural Dynamics by Matthew M. Williamson M.Eng, University of Oxford (1993) S.M., Massachusetts Institute of Technology (1995) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 1999 c Massachusetts Institute of Technology 1999 SignatureofAuthor............................................................... Department of Electrical Engineering and Computer Science May 18, 1999 Certifiedby........................................................................ Rodney A. Brooks Professor of Electrical Engineering and Computer Science, MIT Thesis Supervisor Accepted by . ...................................................................... Arthur C. Smith Chairman, Departmental Committee on Graduate Students Robot Arm Control Exploiting Natural Dynamics by Matthew M. Williamson Revised version of a thesis submitted to the Department of Electrical Engineering and Computer Science on May 18, 1999, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract This thesis presents an approach to robot arm control exploiting natural dynamics. The approach consists of using a compliant arm whose joints are controlled with simple non-linear oscillators. The arm has special actuators which makes it robust to collisions and gives it a smooth compliant motion. The oscillators produce rhythmic commands of the joints of the arm, and feedback
    [Show full text]
  • Development of an Active High-Speed 3-D Vision System †
    sensors Article Development of an Active High-Speed 3-D Vision System † Akio Namiki 1,* , Keitaro Shimada 1, Yusuke Kin 1 and Idaku Ishii 2 1 Department of Mechanical Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan; [email protected] (K.S.); [email protected] (Y.K.) 2 Department of System Cybernetics, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-43-290-3194 † This paper is an extended version of the conference paper: High-speed 3-D measurement of a moving object with visual servo. In Proceedings of 2016 IEEE/SICE International Symposium on System Integration (SII), Sapporo, Japan, 13–15 December 2016 and High-speed orientation measurement of a moving object with patterned light projection and model matching. In Proceedings of 2018 IEEE Conference on Robotics and Biomimetics (ROBIO), Kuala Lumpur, Malaysia, 12–15 December 2018. Received: 1 February 2019; Accepted: 22 March 2019; Published: 1 April 2019 Abstract: High-speed recognition of the shape of a target object is indispensable for robots to perform various kinds of dexterous tasks in real time. In this paper, we propose a high-speed 3-D sensing system with active target-tracking. The system consists of a high-speed camera head and a high-speed projector, which are mounted on a two-axis active vision system. By measuring a projected coded pattern, 3-D measurement at a rate of 500 fps was achieved. The measurement range was increased as a result of the active tracking, and the shape of the target was accurately observed even when it moved quickly.
    [Show full text]
  • Using Closed Feedback Loops to Evaluate Autonomous Juggling Performance
    Using Closed Feedback Loops to Evaluate Autonomous Juggling Performance Tomas´ Collado Hamzah Farooqi [email protected] [email protected] Tashu Gupta Ashwindev Pazhetam Robert Taylor [email protected] [email protected] [email protected] Kevin Ge* [email protected] New Jersey’s Governor’s School of Engineering and Technology July 18, 2020 *Corresponding Author Abstract—Juggling requires humans to intake a vast amount of This project aspires to study the complex movements of visual information, analyze it, and act accordingly, all at a speed humans, particularly in juggling, and recreate them through a that seems to surpass normal human reaction time. To study simulated robot. Once a juggling robot is completed, the goal these dexterous human movements, this project aims to recreate juggling through a simulated robot that inputs feedback similar of the project is to determine the minimum amount of feedback to how a human would. In this project, a robot was developed necessary to complete a successful juggle. By incrementally using a game development engine called Unity that performed a limiting the amount of information the robot receives, the three ball cascade based on knowledge of the positions of the balls necessity of certain data will be determined which will allow at all times, and, when this knowledge was restricted, was able to for the creation of more dexterous and efficient feedback- juggle using the initial velocities of the balls and simulated visual feedback. Comparing the two feedback systems yielded a better dependent robots. understanding as to how humans juggle, as well as how robots can be improved to perform advanced, dexterous movements.
    [Show full text]
  • Toward the Control of Attention in a Dynamically Dexterous Robot*
    of the 1993 IEEURSJ International Conference on Intelligent Robots and Systems Yokohama,Japan July 2630,1993 Toward the Control of Attention in a Dynamically Dexterous Robot* A. A. Rizzi +and D. E. Koditschek University of Michigan, Artificial Intelligence Laboratory Department of Electrical Engineering and Computer Science Abs t kact ’ recent successful effort to achieve the spatial two- batting two freely falling balls into independent Figure 1: The Yale Spatial Juggler [lo] 1 dtroduction must stress considerations of update and latency over mere throughput. Moreover, the process of extracting a little in- formation from a lot of data is driven toward the minimum that will suffice for the task at hand rather than striving for the most that might logically be had. Finally, when previously sensed data mediates the collection of new in- formation, a stability problem may result. The architecture of our original setup is briefly reviewed in Section 2. The recent success of the two-juggle could not have found that there is already enough room have been achieved without the enhancements to the vision in getting its management right as to presage system that we describe in Section 3. Although the work- important and novel problems that might be ing enhancements were developed in an ad hoc manner and implemented through a process of empirical trial and error, we suspect that the resulting system (or, at least, a suitably polished version thereof) should admit a relatively simple formal description. In Section 4 we present our progress in particularly simple case. rendering such a formal description with the hope of pro- moting a more principled approach to solving such sensory control problems when we encounter them in the future.
    [Show full text]