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      An Overview on Principles for Energy Efficient Robot Locomotion

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          Abstract

          Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

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          Most cited references107

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          Passive Dynamic Walking

          T McGeer (1990)
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            Central pattern generators for locomotion control in animals and robots: a review.

            The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed.
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              Efficient bipedal robots based on passive-dynamic walkers.

              Passive-dynamic walkers are simple mechanical devices, composed of solid parts connected by joints, that walk stably down a slope. They have no motors or controllers, yet can have remarkably humanlike motions. This suggests that these machines are useful models of human locomotion; however, they cannot walk on level ground. Here we present three robots based on passive-dynamics, with small active power sources substituted for gravity, which can walk on level ground. These robots use less control and less energy than other powered robots, yet walk more naturally, further suggesting the importance of passive-dynamics in human locomotion.
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                Author and article information

                Contributors
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                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                11 December 2018
                2018
                : 5
                : 129
                Affiliations
                [1] 1Humanoids and Human Centred Mechatronics Lab, Department of Advanced Robotics, Istituto Italiano di Tecnologia , Genova, Italy
                [2] 2Dynamic Robotics Laboratory, School of MIME, Oregon State University , Corvallis, OR, United States
                [3] 3Department of Biomedical Physiology and Kinesiology, Simon Fraser University , Burnaby, BC, Canada
                [4] 4Robotics and Mechatronics Center, German Aerospace Center , Oberpfaffenhofen, Germany
                [5] 5Structure and Motion Laboratory, Royal Veterinary College , Hertfordshire, United Kingdom
                [6] 6Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne , Lausanne, Switzerland
                [7] 7Robotics and Multibody Mechanics Research Group, Department of Mechanical Engineering, Vrije Universiteit Brussel and Flanders Make , Brussels, Belgium
                [8] 8Centro di Ricerca “Enrico Piaggio”, University of Pisa , Pisa, Italy
                [9] 9Robotics Institute, Carnegie Mellon University , Pittsburgh, PA, United States
                [10] 10Applied Biomechanics Lab, Department of Integrative Physiology, University of Colorado , Boulder, CO, United States
                [11] 11Robotics and Motion Laboratory, Department of Mechanical Engineering, University of Michigan , Ann Arbor, MI, United States
                [12] 12Department of Mechanical Engineering, Korea University , Seoul, South Korea
                [13] 13Control Engineering group, University of Twente , Enschede, Netherlands
                Author notes

                Edited by: Francesco Becchi, Danieli Telerobot Labs, Italy

                Reviewed by: Wiktor Sieklicki, Gdańsk University of Technology, Poland; Giovanni Stellin, Danieli Telerobot Labs, Italy

                *Correspondence: Navvab Kashiri navvab.kashiri@ 123456iit.it

                This article was submitted to Humanoid Robotics, a section of the journal Frontiers in Robotics and AI

                Article
                10.3389/frobt.2018.00129
                7805619
                33501007
                e3d12eda-419f-40ae-a590-392bd8422c8e
                Copyright © 2018 Kashiri, Abate, Abram, Albu-Schaffer, Clary, Daley, Faraji, Furnemont, Garabini, Geyer, Grabowski, Hurst, Malzahn, Mathijssen, Remy, Roozing, Shahbazi, Simha, Song, Smit-Anseeuw, Stramigioli, Vanderborght, Yesilevskiy and Tsagarakis.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 March 2018
                : 01 November 2018
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 107, Pages: 13, Words: 12111
                Categories
                Robotics and AI
                Review

                variable impedance actuators,energy efficiency,energetics,cost of transport,locomotion principles,bio-inspired motions

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