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[Online] Robotics

Guest Editorial Board (2017)
Guest Editors-in-Chief 
Tianran Wang, Shenyang Institute of Automation, Chinese Academy of Sciences
Executive Associate Editors
Tianmiao Wang, Beihang University, China
Ning Xi, Michigan State University, USA
Han Ding, Huazhong University of Science and Technology, China
Kazihiro Kosuge, Tohoku University, Japan
Matin Buss, Technical University of Munich, Germany
Oussama Khatib, Stanford University, USA
Paolo Dario, the Bio-Robotics Institute of the Scuola Superiore Sant'Anna, Italy
Peter Corke, Queensland University of Technology, Australia
Raja Chatila, Université Pierre et Marie Curie, France
Richard Vaughan, Simon Fraser University, Canada
Robert Woods, Harvard University, USA
William R. Hamel, University of Tennessee, USA

Guest Editorial Board (2015)
Guest Editors-in-Chief
Xu, Yangsheng, The Chinese University of Hong Kong (Shenzhen), China
Nelson, Bradley, Eidgen?ssische Technische Hochschule Zürich, Switzerland
Bergerman, Marcel, Carnegie Mellon University, USA
Cai, Hegao, Harbin Institute of Technology, China
Fukuda, Toshio, Nagoya University, Japan
Khatib, Oussama, Stanford University, USA
Kumar, Vijay, University of Pennsylvania, USA
Manocha, Dinesh, University of North Carolina at Chapel Hill, USA
Tarn, Tzyh-Jong, Washington University, USA
Xiong, Youlun, Huazhong University of Science and Technology, China
Zhang, Hong, University of Alberta, Canada
Zheng, Yuanfang, The Ohio State University at Columbus, USA
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Decentralized Searching of Multiple Unknown and Transient Radio Sources with Paired Robots
Chang-Young Kim, Dezhen Song, Jingang Yi, Xinyu Wu
Engineering    2015, 1 (1): 58-65.
Abstract   HTML   PDF (1690KB)

In this paper, we develop a decentralized algorithm to coordinate a group of mobile robots to search for unknown and transient radio sources. In addition to limited mobility and ranges of communication and sensing, the robot team has to deal with challenges from signal source anonymity, short transmission duration, and variable transmission power. We propose a two-step approach: First, we decentralize belief functions that robots use to track source locations using checkpoint-based synchronization, and second, we propose a decentralized planning strategy to coordinate robots to ensure the existence of checkpoints. We analyze memory usage, data amount in communication, and searching time for the proposed algorithm. We have implemented the proposed algorithm and compared it with two heuristics. The experimental results show that our algorithm successfully trades a modest amount of memory for the fastest searching time among the three methods.

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Efficient Configuration Space Construction and Optimization for Motion Planning
Jia Pan, Dinesh Manocha
Engineering    2015, 1 (1): 46-57.
Abstract   HTML   PDF (2919KB)

The configuration space is a fundamental concept that is widely used in algorithmic robotics. Many applications in robotics, computer-aided design, and related areas can be reduced to computational problems in terms of configuration spaces. In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: ① how to efficiently compute an approximate representation of high-dimensional configuration spaces; and ② how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces. We present new configuration space construction algorithms based on machine learning and geometric approximation techniques. These algorithms perform collision queries on many configuration samples. The collision query results are used to compute an approximate representation for the configuration space, which quickly converges to the exact configuration space. We also present parallel GPU-based algorithms to accelerate the performance of optimization and search computations in configuration spaces. In particular, we design efficient GPU-based parallel k-nearest neighbor and parallel collision detection algorithms and use these algorithms to accelerate motion planning.

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DARPA Robotics Grand Challenge Participation and Ski-Type Gait for Rough-Terrain Walking
Hongfei Wang, Shimeng Li, Yuan F. Zheng
Engineering    2015, 1 (1): 36-45.
Abstract   HTML   PDF (2440KB)

In this paper, we briefly introduce the history of the Defense Advanced Research Projects Agency (DARPA) Grand Challenge programs with particular focus on the 2012 Robotics Challenge. As members of team DRC-HUBO, we propose different approaches for the Rough-Terrain task, such as enlarged foot pedals and a transformation into quadruped walking. We also introduce a new gait for humanoid robot locomotion to improve stability performance, called the Ski-Type gait. We analyze the stability performance of this gait and use the stability margin to choose between two candidate step sequences, Crawl-1 and Crawl-2. Next, we perform a force/torque analysis for the redundant closed-chain system in the Ski-Type gait, and determine the joint torques by minimizing the total energy consumption. Based on the stability and force/torque analysis, we design a cane length to support a feasible and stable Crawl-2 gait on the HUBO2 humanoid robot platform. Finally, we compare our experimental results with biped walking to validate the Ski-Type gait. We also present our team performance in the trials of the Robotics Challenge.

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Architecture and Software Design for a Service Robot in an Elderly-Care Scenario
Norman Hendrich, Hannes Bistry, Jianwei Zhang
Engineering    2015, 1 (1): 27-35.
Abstract   HTML   PDF (8114KB)

Systems for ambient assisted living (AAL) that integrate service robots with sensor networks and user monitoring can help elderly people with their daily activities, allowing them to stay in their homes and live active lives for as long as possible. In this paper, we outline the AAL system currently developed in the European project Robot-Era, and describe the engineering aspects and the service-oriented software architecture of the domestic robot, a service robot with advanced manipulation capabilities. Based on the robot operating system (ROS) middleware, our software integrates a large set of advanced algorithms for navigation, perception, and manipulation. In tests with real end users, the performance and acceptability of the platform are evaluated.

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Magnetic Helical Micro- and Nanorobots: Toward Their Biomedical Applications
Famin Qiu, Bradley J. Nelson
Engineering    2015, 1 (1): 21-26.
Abstract   HTML   PDF (3873KB)

Magnetic helical micro- and nanorobots can perform 3D navigation in various liquids with a sub-micrometer precision under low-strength rotating magnetic fields (<10 mT). Since magnetic fields with low strengths are harmless to cells and tissues, magnetic helical micro/nanorobots are promising tools for biomedical applications, such as minimally invasive surgery, cell manipulation and analysis, and targeted therapy. This review provides general information on magnetic helical micro/nanorobots, including their fabrication, motion control, and further functionalization for biomedical applications.

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Vibration-Driven Microrobot Positioning Methodologies for Nonholonomic Constraint Compensation
Kostas Vlachos, Dimitris Papadimitriou, Evangelos Papadopoulos
Engineering    2015, 1 (1): 66-72.
Abstract   HTML   PDF (3430KB)

This paper presents the formulation and practical implementation of positioning methodologies that compensate for the nonholonomic constraints of a mobile microrobot that is driven by two vibrating direct current (DC) micromotors. The open-loop and closed-loop approaches described here add the capability for net sidewise displacements of the microrobotic platform. A displacement is achieved by the execution of a number of repeating steps that depend on the desired displacement, the speed of the micromotors, and the elapsed time. Simulation and experimental results verified the performance of the proposed methodologies.

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Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
Kun Li, Max Q.-H. Meng
Engineering    2015, 1 (1): 79-84.
Abstract   HTML   PDF (1714KB)

For a domestic personal robot, personalized services are as important as predesigned tasks, because the robot needs to adjust the home state based on the operator’s habits. An operator’s habits are composed of cues, behaviors, and rewards. This article introduces behavioral footprints to describe the operator’s behaviors in a house, and applies the inverse reinforcement learning technique to extract the operator’s habits, represented by a reward function. We implemented the proposed approach with a mobile robot on indoor temperature adjustment, and compared this approach with a baseline method that recorded all the cues and behaviors of the operator. The result shows that the proposed approach allows the robot to reveal the operator’s habits accurately and adjust the environment state accordingly.

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A Novel Tele-Operated Flexible Robot Targeted for Minimally Invasive Robotic Surgery
Zheng Li, Jan Feiling, Hongliang Ren, Haoyong Yu
Engineering    2015, 1 (1): 73-78.
Abstract   HTML   PDF (3530KB)

In this paper, a novel flexible robot system with a constrained tendon-driven serpentine manipulator (CTSM) is presented. The CTSM gives the robot a larger workspace, more dexterous manipulation, and controllable stiffness compared with the da Vinci surgical robot and traditional flexible robots. The robot is tele-operated using the Novint Falcon haptic device. Two control modes are implemented, direct mapping and incremental mode. In each mode, the robot can be manipulated using either the highest stiffness scheme or the minimal movement scheme. The advantages of the CTSM are shown by simulation and experimental results.

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