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[Online] Robotics

Guest Editorial Board (2018)
Guest Editors-in-Chief 
Tianran Wang, Shenyang Institute of Automation, Chinese Academy of Sciences
 
Executive Editors-in-Chief
Wang, Tianmiao, Beihang University, China
Xi, Ning, The University of Hong Kong, China
 
Members
Buss, Matin, Technical University of Munich, Germany
Chatila, Raja, Université Pierre et Marie Curie, France
Corke, Peter, Queensland University of Technology, Australia
Dario, Paolo, The BioRobotics Institute, Sant’Anna School of Advanced Studies, Italy
Ding, Han, Huazhong University of Science and Technology, China
Hamel, William R., The University of Tennessee, USA
Khatib, Oussama, Stanford University, USA
Kosuge, Kazihiro, Tohoku University, Japan
Vaughan, Richard, Simon Fraser University, Canada
Woods, Robert, Harvard University, 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
 
Members
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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Development and Future Challenges of Bio-Syncretic Robots
Chuang Zhang, Wenxue Wang, Ning Xi, Yuechao Wang, Lianqing Liu
Engineering    2018, 4 (4): 452-463.   https://doi.org/10.1016/j.eng.2018.07.005
Abstract   PDF (938KB)

Bio-syncretic robots consisting of both living biological materials and non-living systems possess desirable attributes such as high energy efficiency, intrinsic safety, high sensitivity, and self-repairing capabilities. Compared with living biological materials or non-living traditional robots based on electromechanical systems, the combined system of a bio-syncretic robot holds many advantages. Therefore, developing bio-syncretic robots has been a topic of great interest, and significant progress has been achieved in this area over the past decade. This review systematically summarizes the development of bio-syncretic robots. First, potential trends in the development of bio-syncretic robots are discussed. Next, the current performance of bio-syncretic robots, including simple movement and controllability of velocity and direction, is reviewed. The living biological materials and non-living materials that are used in bio-syncretic robots, and the corresponding fabrication methods, are then discussed. In addition, recently developed control methods for bio-syncretic robots, including physical and chemical control methods, are described. Finally, challenges in the development of bio-syncretic robots are discussed from multiple viewpoints, including sensing and intelligence, living and non-living materials, control approaches, and information technology.

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A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain
Deyi Li, Hongbo Gao
Engineering    2018, 4 (4): 464-470.   https://doi.org/10.1016/j.eng.2018.07.015
Abstract   PDF (1936KB)

The type, model, quantity, and location of sensors installed on the intelligent vehicle test platform are different, resulting in different sensor information processing modules. The driving map used in intelligent vehicle test platform has no uniform standard, which leads to different granularity of driving map information. The sensor information processing module is directly associated with the driving map information and decision-making module, which leads to the interface of intelligent driving system software module has no uniform standard. Based on the software and hardware architecture of intelligent vehicle, the sensor information and driving map information are processed by using the formal language of driving cognition to form a driving situation graph cluster and output to a decision-making module, and the output result of the decision-making module is shown as a cognitive arrow cluster, so that the whole process of intelligent driving from perception to decision-making is completed. The formalization of driving cognition reduces the influence of sensor type, model, quantity, and location on the whole software architecture, which makes the software architecture portable on different intelligent driving hardware platforms.

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Unpowered Knee Exoskeleton Reduces Quadriceps Activity during Cycling
Ronnapee Chaichaowarat, Jun Kinugawa, Kazuhiro Kosuge
Engineering    2018, 4 (4): 471-478.   https://doi.org/10.1016/j.eng.2018.07.011
Abstract   PDF (3420KB)

Cycling is an eco-friendly method of transport and recreation. With the intent of reducing the energy cost of cycling without providing an additional energy source, we have proposed the use of a torsion spring for knee-extension support. We developed an exoskeleton prototype using a crossing four-bar mechanism as a knee joint with an embedded torsion spring. This study evaluates the passive knee exoskeleton using constant-power cycling tests performed by eight healthy male participants. We recorded the surface electromyography over the rectus femoris muscles of both legs, while the participants cycled at 200 and 225W on a trainer with the developed wheel-accelerating system. We then analyzed these data in time–frequency via a continuous wavelet transform. At the same cycling speed and leg cadence, the median power spectral frequency of the electromyography increases with cycling load. At the same cycling load, the median power spectral frequency decreases when cycling with the exoskeleton. Quadriceps activity can be relieved despite the exoskeleton consuming no electrical energy and not delivering net-positive mechanical work. This fundamental can be applied to the further development of wearable devices for cycling assistance.

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A Co-Point Mapping-Based Approach to Drivable Area Detection for Self-Driving Cars
Ziyi Liu, Siyu Yu, Nanning Zheng
Engineering    2018, 4 (4): 479-490.   https://doi.org/10.1016/j.eng.2018.07.010
Abstract   PDF (4008KB)

The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas. Inspired by human driving behaviors, we propose a novel method of drivable area detection for self-driving cars based on fusing pixel information from a monocular camera with spatial information from a light detection and ranging (LIDAR) scanner. Similar to the bijection of collineation, a new concept called co-point mapping, which is a bijection that maps points from the LIDAR scanner to points on the edge of the image segmentation, is introduced in the proposed method. Our method positions candidate drivable areas through self-learning models based on the initial drivable areas that are obtained by fusing obstacle information with superpixels. In addition, a fusion of four features is applied in order to achieve a more robust performance. In particular, a feature called drivable degree (DD) is proposed to characterize the drivable degree of the LIDAR points. After the initial drivable area is characterized by the features obtained through self-learning, a Bayesian framework is utilized to calculate the final probability map of the drivable area. Our approach introduces no common hypothesis and requires no training steps; yet it yields a state-of-art performance when tested on the ROAD-KITTI benchmark. Experimental results demonstrate that the proposed method is a general and efficient approach for detecting drivable area.

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Control of Velocity-Constrained Stepper Motor-Driven Hilare Robot for Waypoint Navigation
Robins Mathew, Somashekhar S. Hiremath
Engineering    2018, 4 (4): 491-499.   https://doi.org/10.1016/j.eng.2018.07.013
Abstract   PDF (1659KB)

Finding an optimal trajectory from an initial point to a final point through closely packed obstacles, and controlling a Hilare robot through this trajectory, are challenging tasks. To serve this purpose, path planners and trajectory-tracking controllers are usually included in a control loop. This paper highlights the implementation of a trajectory-tracking controller on a stepper motor-driven Hilare robot, with a trajectory that is described as a set of waypoints. The controller was designed to handle discrete waypoints with directional discontinuity and to consider different constraints on the actuator velocity. The control parameters were tuned with the help of multi-objective particle swarm optimization to minimize the average cross-track error and average linear velocity error of the mobile robot when tracking a predefined trajectory. Experiments were conducted to control the mobile robot from a start position to a destination position along a trajectory described by the waypoints. Experimental results for tracking the trajectory generated by a path planner and the trajectory specified by a user are also demonstrated. Experiments conducted on the mobile robot validate the effectiveness of the proposed strategy for tracking different types of trajectories.

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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.   https://doi.org/10.15302/J-ENG-2015010
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.   https://doi.org/10.15302/J-ENG-2015009
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.   https://doi.org/10.15302/J-ENG-2015006
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.   https://doi.org/10.15302/J-ENG-2015007
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.   https://doi.org/10.15302/J-ENG-2015005
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.   https://doi.org/10.15302/J-ENG-2015016
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.   https://doi.org/10.15302/J-ENG-2015024
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.   https://doi.org/10.15302/J-ENG-2015011
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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