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Iterative learning of energy-efficient dynamic walking gaits

Iterative learning of energy-efficient dynamic walking gaits

引用

25th ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Kong, Felix H. Manchester, Ian R. Univ Sydney Australian Ctr Field Robot Sydney NSW 2006 Australia

ISBN: (纸本)9781538680940

Dynamic walking robots have the potential for efficient and lifelike locomotion, but computing efficient gaits and tracking them is difficult in the presence of under-modeling. Iterative Learning Control (ILC) is a method to learn the control signal to track a periodic reference over several attempts, augmenting a model with online data. Terminal ILC (TILC), a variant of ILC, allows other performance objectives to be addressed at the cost of ignoring parts of the reference. However, dynamic walking robot gaits are not necessarily periodic in time. In this paper, we adapt TILC to jointly optimize final foot placement and energy efficiency on dynamic walking robots by indexing by a phase variable instead of time, yielding "phase-indexed TILC" (theta-TILC). When implemented on a five-link walker in simulation, theta-TILC learns a more energy-efficient walking motion compared to traditional time-indexed TILC.

关键词： Legged locomotion Computational modeling Data models Foot Planning Convergence

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A Framework for Depth Estimation and Relative Localization of Ground robots using Computer Vision

A Framework for Depth Estimation and Relative Localization o...

引用

2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Rômulo T. Rodrigues Pedro Miraldo Dimos V. Dimarogonas A. Pedro Aguiar Research Center for Systems and Technologies (SYSTEC) Faculty of Engineering University of Porto Porto Portugal Devision of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden

The 3D depth estimation and relative pose estimation problem within a decentralized architecture is a challenging problem that arises in missions that require coordination among multiple vision-controlled robots. The depth estimation problem aims at recovering the 3D information of the environment. The relative localization problem consists of estimating the relative pose between two robots, by sensing each other's pose or sharing information about the perceived environment. Most solutions for these problems use a set of discrete data without taking into account the chronological order of the events. This paper builds on recent results on continuous estimation to propose a framework that estimates the depth and relative pose between two non-holonomic vehicles. The basic idea consists in estimating the depth of the points by explicitly considering the dynamics of the camera mounted on a ground robot, and feeding the estimates of 3D points observed by both cameras in a filter that computes the relative pose between the robots. We evaluate the convergence for a set of simulated scenarios and show experimental results validating the proposed framework.

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Design, Modeling and Testing of a Flagellum-inspired Soft Underwater Propeller Exploiting Passive Elasticity

Design, Modeling and Testing of a Flagellum-inspired Soft Un...

引用

2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Marcello Calisti Francesco Giorgio-Serchi Cesare Stefanini Madiha Farman Irfan Hussain Costanza Armanini Dongming Gan Lakmal Seneviratne Federico Renda The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Institute of Integrated Micro and Nano Systems of the University of Edinburgh Edinburgh UK Khalifa University Center for Autonomous Robotic Systems (KUCARS) Khalifa University of Science and Technology Abu Dhabi UAE

Flagellated micro-organism are regarded as excellent swimmers within their size scales. This, along with the simplicity of their actuation and the richness of their dynamics makes them a valuable source of inspiration to design continuum, self-propelled underwater robots. Here we introduce a soft, flagellum-inspired system which exploits the compliance of its own body to passively attain a range of geometrical configurations from the interaction with the surrounding fluid. The spontaneous formation of stable helical waves along the length of the flagellum is responsible for the generation of positive net thrust. We investigate the relationship between actuation frequency and material elasticity in determining the steady-state configuration of the system and its thrust output. This is ultimately used to perform a parameter identification procedure of an elastodynamic model aimed at investigating the scaling laws in the propulsion of flagellated robots.

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Graph-based Path Planning for Autonomous Robotic Exploration in Subterranean Environments

Graph-based Path Planning for Autonomous Robotic Exploration...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Tung Dang Frank Mascarich Shehryar Khattak Christos Papachristos Kostas Alexis Autonomous Robots Lab University of Nevada Reno 1664 N. Virginia 89557 Reno NV USA

This paper presents a novel strategy for autonomous graph-based exploration path planning in subterranean environments. Attuned to the fact that subterranean settings, such as underground mines, are often large-scale networks of narrow tunnel-like and multi-branched topologies, the proposed planner is structured around a bifurcated local-and global-planner architecture. The local planner employs a rapidly-exploring random graph to reliably and efficiently identify collision-free paths that optimize an exploration gain within a local subspace. Accounting for the robot endurance limitations and the possibility that the local planner reaches a dead-end (e.g. a mine heading), the global planner is engaged when a return-to-home path must be derived or when the robot should be re-positioned towards an edge of the exploration space. The proposed planner is field evaluated in a collection of deployments inside both active and abandoned underground mines in the U.S. and in Switzerland.

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Dynamic Control of Soft robots with Internal Constraints in the Presence of Obstacles

Dynamic Control of Soft Robots with Internal Constraints in ...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Cosimo Della Santina Antonio Bicchi Daniela Rus Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology 32 Vassar St Cambridge MA USA Research Center “E. Piaggio” and the University of Pisa Italy

The development of effective reduced order models for soft robots is paving the way toward the development of a new generation of model based techniques, which leverage classic rigid robot control. However, several soft robot features differentiate the soft-bodied case from the rigid-bodied one. First, soft robots are built to work in the environment, so the presence of obstacles in their path should always be explicitly accounted by their control systems. Second, due to the complex kinematics, the actuation of soft robots is mapped to the state space nonlinearly resulting in spaces with different sizes. Moreover, soft robots often include internal constraints and thus actuation is typically limited in the range of action and it is often unidirectional. This paper proposes a control pipeline to tackle the challenge of controlling soft robots with internal constraints in environments with obstacles. We show how the constraints on actuation can be propagated and integrated with geometrical constraints, taking into account physical limits imposed by the presence of obstacles. We present a hierarchical control architecture capable of handling these constraints, with which we are able to regulate the position in space of the tip of a soft robot with the discussed characteristics.

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Component Modularized Design of Musculoskeletal Humanoid Platform Musashi to Investigate Learning Control systems

Component Modularized Design of Musculoskeletal Humanoid Pla...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Kento Kawaharazuka Shogo Makino Kei Tsuzuki Moritaka Onitsuka Yuya Nagamatsu Koki Shinjo Tasuku Makabe Yuki Asano Kei Okada Koji Kawasaki Masayuki Inaba Department of Mechano-Informatics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan TOYOTA MOTOR CORPORATION

To develop Musashi as a musculoskeletal humanoid platform to investigate learning control systems, we aimed for a body with flexible musculoskeletal structure, redundant sensors, and easily reconfigurable structure. For this purpose, we develop joint modules that can directly measure joint angles, muscle modules that can realize various muscle routes, and nonlinear elastic units with soft structures, etc. Next, we develop MusashiLarm, a musculoskeletal platform composed of only joint modules, muscle modules, generic bone frames, muscle wire units, and a few attachments. Finally, we develop Musashi, a musculoskeletal humanoid platform which extends MusashiLarm to the whole body design, and conduct several basic experiments and learning control experiments to verify the effectiveness of its concept.

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Modelling of Uniaxial EGaIn-Based Strain Sensors for Proprioceptive Sensing of Soft robots

Modelling of Uniaxial EGaIn-Based Strain Sensors for Proprio...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Abdullah Al-Azzawi A. Mounir Boudali He Kong Ali H. Göktoğan Salah Sukkarieh Australian Centre for Field Robotics (ACFR) The University of Sydney NSW Australia

Soft strain resistive sensors based on eutectic gallium-indium liquid metal can play an important role in proprioceptive sensing for soft robots. However, there are no available mathematical models to accurately estimate the strain as a function of the measured resistance. Furthermore, non-uniform strain in the microchannels has not been analysed yet. In this paper, we introduce a new model to estimate the strain or elongation in sub-millimetre scale, and analyse its accuracy through a customised testing set-up and procedure. The effect of strain rate on the measurement accuracy is also studied. We compare existing theoretical models with our experimental results, and discuss the differences between them. Moreover, we analyse the effect of strain rate on hysteresis caused by the viscoelastic behaviour and introduce a new model for it to be potentially used for future work. This paper demonstrates, among other things, that rational models could provide high accuracy in strain estimation, and might help to enhance proprioceptive sensing and state control of soft robots.

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Situation Awareness for Proactive robots in HRI

Situation Awareness for Proactive Robots in HRI

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Chapa Sirithunge H. M. Ravindu T. Bandara A. G. Buddhika P. Jayasekara D. P. Chandima The Intelligent Service Robotics Group Department of Electrical Engineering University of Moratuwa Katubedda Sri Lanka

Perception of the intention of humans prior to an interaction is a demanding skill during human-robot interaction (HRI). This skill is even more sought after during robot-initiated HRI. Initiating an interaction in an inappropriate situation can be avoided when robots are equipped with the ability to decide when to interact and when not to. Many of the existing systems investigate only a few characteristics of humans which demonstrate inner state of mind and are based on complex monitoring mechanisms which limit their use in most of the scenarios. This work presents an autoregressive model based on observable physical and emotional human cues to determine the level of interest displayed by a human towards an interaction with a robot. This model was implemented on a service robotic platform and the behavior of the robot was controlled using the model. The behavior of the robot was determined by means of proxemic approach and the nature of conversation with the human. The outcomes of the model were evaluated by analyzing user feedback in different situations inside a simulated social environment. Using the model, robot was given the ability to analyze the situation of its human user in an emotionally intelligent manner, prior to an interaction. The behavior of the model was reviewed by user feedback in order to validate the findings. Results of the experiment are presented and findings of the study are discussed.

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Small-Scale Compliant Dual Arm with Tail for Winged Aerial robots

Small-Scale Compliant Dual Arm with Tail for Winged Aerial R...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Alejandro Suarez Manuel Perez Guillermo Heredia Anibal Ollero GRVC Robotics Labs University of Seville Spain

Winged aerial robots represent an evolution of aerial manipulation robots, replacing the multirotor vehicles by fixed or flapping wing platforms. The development of this morphology is motivated in terms of efficiency, endurance and safety in some inspection operations where multirotor platforms may not be suitable. This paper presents a first prototype of compliant dual arm as preliminary step towards the realization of a winged aerial robot capable of perching and manipulating with the wings folded. The dual arm provides 6 DOF (degrees of freedom) for end effector positioning in a human-like kinematic configuration, with a reach of 25 cm (half-scale w.r.t. the human arm), and 0.2 kg weight. The prototype is built with micro metal gear motors, measuring the joint angles and the deflection with small potentiometers. The paper covers the design, electronics, modeling and control of the arms. Experimental results in test-bench validate the developed prototype and its functionalities, including joint position and torque control, bimanual grasping, the dynamic equilibrium with the tail, and the generation of 3D maps with laser sensors attached at the arms.

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Infrastructure-free NLoS Obstacle Detection for Autonomous Cars

Infrastructure-free NLoS Obstacle Detection for Autonomous C...

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2019 ieee/rsj international conference on intelligent robots and systems (IROS)

作者： Felix Naser Igor Gilitschenski Alexander Amini Christina Liao Guy Rosman Sertac Karaman Daniela Rus Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute for Technology Cambridge MA USA Toyota Research Institute (TRI) Cambridge MA USA Laboratory for Information and Decision Systems (LIDS) Massachusetts Institute for Technology Cambridge MA USA

Current perception systems mostly require direct line of sight to anticipate and ultimately prevent potential collisions at intersections with other road users. We present a fully integrated autonomous system capable of detecting shadows or weak illumination changes on the ground caused by a dynamic obstacle in NLoS scenarios. This additional virtual sensor “ShadowCam” extends the signal range utilized so far by computer-vision ADASs. We show that (1) our algorithm maintains the mean classification accuracy of around 70% even when it doesn't rely on infrastructure - such as AprilTags - as an image registration method. We validate (2) in real-world experiments that our autonomous car driving in night time conditions detects a hidden approaching car earlier with our virtual sensor than with the front facing 2-D LiDAR.

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