Journal of Robotics The latest articles from Hindawi © 2017 , Hindawi Limited . All rights reserved. Generation and Control of Basic Geometric Trajectories for a Robot Manipulator Using CompactRIO® Mon, 11 Dec 2017 00:00:00 +0000 The utility of a robot manipulator focuses on the ability to locate its end effector in a position with a determined orientation following a specified trajectory. For this, algorithms were used in order to generate and control the movements joints of robot in a synchronized way. The high-level languages to program robots are based on three types of movement: joint interpolation (MOVEJ), linear interpolation (MOVES), and circular arcs (MOVEC), which are used to develop any type of task. In this work, these three movements are implemented in the industrial controller CompactRIO, as part of the reconditioning process of a robot manipulator of five degrees of freedom (5 DOF) whose controller was obsolete. As a result, it will have an interface in LabVIEW where you can view and modify the basic parameters implemented in the industrial controller. In addition, the results of the validation tests of the joint positions and the end effector of the manipulator will be found. Jorge Luis Aroca Trujillo, Alexander Pérez-Ruiz, and Ruthber Rodriguez Serrezuela Copyright © 2017 Jorge Luis Aroca Trujillo et al. All rights reserved. Hierarchical Sliding Mode Algorithm for Athlete Robot Walking Wed, 06 Dec 2017 00:00:00 +0000 Dynamic equations and the control law for a class of robots with elastic underactuated MIMO system of legs, athlete Robot, are discussed in this paper. The dynamic equations are determined by Euler-Lagrange method. A new method based on hierarchical sliding mode for controlling postures is also introduced. Genetic algorithm is applied to design the oscillator for robot motion. Then, a hierarchical sliding mode controller is implemented to control basic posture of athlete robot stepping. Successful simulation results show the motion of athlete robot. Van Dong Hai Nguyen, Xuan-Dung Huynh, Minh-Tam Nguyen, Ionel Cristian Vladu, and Mircea Ivanescu Copyright © 2017 Van Dong Hai Nguyen et al. All rights reserved. Bounded Control of an Actuated Lower-Limb Exoskeleton Sun, 03 Dec 2017 00:00:00 +0000 A bounded control strategy is employed for the rehabilitation and assistance of a patient with lower-limb disorder. Complete and partial lower-limb motor function disorders are considered. This application is centered on the knee and the ankle joint level, thereby considering a user in a sitting position. A high gain observer is used in the estimation of the angular position and angular velocities which is then applied to the estimation of the joint torques. The level of human contribution is feedback of a fraction of the estimated joint torque. This is utilised in order to meet the demands for a bounded human torque; that is, The asymptotic stability of the bounded control law without human contribution and the convergence analysis of the high gain observer is verified using Lyapunov-based analysis. Simulations are performed to verify the proposed control law. Results obtained guarantee a fair trajectory tracking of the physiotherapist trajectory. Michael Oluwatosin Ajayi, Karim Djouani, and Yskandar Hamam Copyright © 2017 Michael Oluwatosin Ajayi et al. All rights reserved. Adaptive Foot in Lower-Limb Prostheses Mon, 20 Nov 2017 00:00:00 +0000 The human foot consists of complex sets of joints. The adaptive nature of the human foot enables it to be stable on any uneven surface. It is important to have such adaptive capabilities in the artificial prosthesis to achieve most of the essential movements for lower-limb amputees. However, many existing lower-limb prostheses lack the adaptive nature. This paper reviews lower-limb adaptive foot prostheses. In order to understand the design concepts of adaptive foot prostheses, the biomechanics of human foot have been explained. Additionally, the requirements and design challenges are investigated and presented. In this review, adaptive foot prostheses are classified according to actuation method. Furthermore, merits and demerits of present-day adaptive foot prostheses are presented based on the hardware construction. The hardware configurations of recent adaptive foot prostheses are analyzed and compared. At the end, potential future developments are highlighted. Thilina H. Weerakkody, Thilina Dulantha Lalitharatne, and R. A. R. C. Gopura Copyright © 2017 Thilina H. Weerakkody et al. All rights reserved. Networked Multimodal Sensor Control of Powered 2-DOF Wrist and Hand Tue, 07 Nov 2017 00:00:00 +0000 A prosthetic limb control system to operate powered 2-DOF wrist and 1-DOF hand with environmental information, myoelectric signal, and forearm posture signal is composed and evaluated. Our concept model on fusing biosignal and environmental information for easier manipulation with upper limb prosthesis is assembled utilizing networking software and prosthetic component interlink platform. The target is to enhance the controllability of the powered wrist’s orientation by processing the information to derive the joint movement in a physiologically appropriate manner. We applied a manipulative skill model of prehension which is constrained by forearm properties, grasping object properties, and task. The myoelectric and forearm posture sensor signals were combined with the work plane posture and the operation mode for grasping object properties. To verify the reduction of the operational load with the proposed method, we conducted 2 performance tests: system performance test to identify the powered 2-DOF wrist’s tracking performance and user operation tests. From the system performance experiment, the fusion control was confirmed to be sufficient to control the wrist joint with respect to the work plane posture. Forearm posture angle ranges were reduced when the prosthesis was operated companying environmental information in the user operation tests. Masaki Shibuya, Kengo Ohnishi, and Isamu Kajitani Copyright © 2017 Masaki Shibuya et al. All rights reserved. Stair Climbing Control for 4-DOF Tracked Vehicle Based on Internal Sensors Wed, 11 Oct 2017 00:00:00 +0000 In search-and-rescue missions, multi-degrees-of-freedom (DOF) tracked robots that are equipped with subtracks are commonly used. These types of robots have superior locomotion performance on rough terrain. However, in teleoperated missions, the performance of tracked robots depends largely on the operators’ ability to control every subtrack appropriately. Therefore, an autonomous traversal function can significantly help in the teleoperation of such robots. In this paper, we propose a planning and control method for 4-DOF tracked robots climbing up/down known stairs automatically based on internal sensors. Experimental results obtained using mockup stairs verify the effectiveness of the proposed method. Daisuke Endo, Atsushi Watanabe, and Keiji Nagatani Copyright © 2017 Daisuke Endo et al. All rights reserved. Corrigendum to “A Wearable Robotic Device Based on Twisted String Actuation for Rehabilitation and Assistive Applications” Wed, 20 Sep 2017 00:00:00 +0000 Mohssen Hosseini, Roberto Meattini, Gianluca Palli, and Claudio Melchiorri Copyright © 2017 Mohssen Hosseini et al. All rights reserved. Long Short-Term Memory Projection Recurrent Neural Network Architectures for Piano’s Continuous Note Recognition Tue, 12 Sep 2017 00:00:00 +0000 Long Short-Term Memory (LSTM) is a kind of Recurrent Neural Networks (RNN) relating to time series, which has achieved good performance in speech recogniton and image recognition. Long Short-Term Memory Projection (LSTMP) is a variant of LSTM to further optimize speed and performance of LSTM by adding a projection layer. As LSTM and LSTMP have performed well in pattern recognition, in this paper, we combine them with Connectionist Temporal Classification (CTC) to study piano’s continuous note recognition for robotics. Based on the Beijing Forestry University music library, we conduct experiments to show recognition rates and numbers of iterations of LSTM with a single layer, LSTMP with a single layer, and Deep LSTM (DLSTM, LSTM with multilayers). As a result, the single layer LSTMP proves performing much better than the single layer LSTM in both time and the recognition rate; that is, LSTMP has fewer parameters and therefore reduces the training time, and, moreover, benefiting from the projection layer, LSTMP has better performance, too. The best recognition rate of LSTMP is . As for DLSTM, the recognition rate can reach because of the effectiveness of the deep structure, but compared with the single layer LSTMP, DLSTM needs more training time. YuKang Jia, Zhicheng Wu, Yanyan Xu, Dengfeng Ke, and Kaile Su Copyright © 2017 YuKang Jia et al. All rights reserved. Corrigendum to “Modular Self-Reconfigurable Robotic Systems: A Survey on Hardware Architectures” Mon, 21 Aug 2017 00:00:00 +0000 S. Sankhar Reddy Chennareddy, Anita Agrawal, and Anupama Karuppiah Copyright © 2017 S. Sankhar Reddy Chennareddy et al. All rights reserved. Modeling and Analysis of Truck Mounted Concrete Pump Boom by Virtual Prototyping Wed, 14 Jun 2017 00:00:00 +0000 By far there is lack of research on different working conditions between rigid and flexible dynamics of truck mounted concrete pump booms. First a 3D model has been established by using virtual prototyping technology of a 37 m long boom in Pro/Engineering software. Then the rigid body simulation model has been built. Next modal superimposition method is adopted to change the 4 rigid body booms into flexible ones. Kinematics law and dynamic characteristics of 4 common working conditions had been studied then. Next tip displacement and the first boom hydraulic cylinder force of the 4 working conditions between rigid and flexible models have been researched. Furthermore the first natural frequencies of the structure have been calculated. The results show that the frequency of the horizontal condition has the lowest of all and the roof condition has the largest of all. Besides the cylinder forces of the flexible model are larger than the corresponding rigid ones because of the flexible boom vibration. Finally an experiment has been done on a boom test rig which proved that the established simulation model is reasonable and the frequency results are correct. All of these provide design reference to mechanical manipulator as well as reducing product development cost of such mechanism. Wu Ren, Zhongwei Li, Yanping Bi, Shan Zhao, Bo Peng, and Liming Zhou Copyright © 2017 Wu Ren et al. All rights reserved. Fuzzy-Sliding Mode Force Control Research on Robotic Machining Thu, 18 May 2017 08:14:27 +0000 The low stiffness has limited the applications of robot to machining process. In this paper, a fuzzy-sliding mode control scheme is proposed to manage the oscillation and chatter appearing in machining operation by adjusting the feed rate. The robotic machining dynamics is first analyzed to identify the parameters with focus on the system stiffness and the behavior during machining process. A controller consisting of a fuzzy estimation enginery which can determine the control gain coefficients according to system status and a sliding mode controller which is used to guarantee convergence and global stability of the system is then proposed. Simulations and experiments results show that, in comparison with open loop and fuzzy-PID control scheme, the fuzzy-sliding mode control scheme can reduce the amplitude and period of oscillation. Shou-yan Chen, Tie Zhang, and Yan-biao Zou Copyright © 2017 Shou-yan Chen et al. All rights reserved. ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps Sun, 09 Apr 2017 10:15:03 +0000 This article presents the implementation and use of a two-wheel autonomous robot and its effectiveness as a tool for studying the recently discovered use of grid cells as part of mammalian’s brains space-mapping circuitry (specifically the medial entorhinal cortex). A proposed discrete-time algorithm that emulates the medial entorhinal cortex is programed into the robot. The robot freely explores a limited laboratory area in the manner of a rat or mouse and reports information to a PC, thus enabling research without the use of live individuals. Position coordinate neural maps are achieved as mathematically predicted although for a reduced number of implemented neurons (i.e., 200 neurons). However, this type of computational embedded system (robot’s microcontroller) is found to be insufficient for simulating huge numbers of neurons in real time (as in the medial entorhinal cortex). It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots. J. Cuneo, L. Barboni, N. Blanco, M. del Castillo, and J. Quagliotti Copyright © 2017 J. Cuneo et al. All rights reserved. Modular Self-Reconfigurable Robotic Systems: A Survey on Hardware Architectures Wed, 15 Mar 2017 08:21:16 +0000 Modular self-reconfigurable robots present wide and unique solutions for growing demands in the domains of space exploration, automation, consumer products, and so forth. The higher utilization factor and self-healing capabilities are most demanded traits in robotics for real world applications and modular robotics offer better solutions in these perspectives in relation to traditional robotics. The researchers in robotics domain identified various applications and prototyped numerous robotic models while addressing constraints such as homogeneity, reconfigurability, form factor, and power consumption. The diversified nature of various modular robotic solutions proposed for real world applications and utilization of different sensor and actuator interfacing techniques along with physical model optimizations presents implicit challenges to researchers while identifying and visualizing the merits/demerits of various approaches to a solution. This paper attempts to simplify the comparison of various hardware prototypes by providing a brief study on hardware architectures of modular robots capable of self-healing and reconfiguration along with design techniques adopted in modeling robots, interfacing technologies, and so forth over the past 25 years. S. Sankhar Reddy Chennareddy, Anita Agrawal, and Anupama Karuppiah Copyright © 2017 S. Sankhar Reddy Chennareddy et al. All rights reserved. Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm Thu, 09 Mar 2017 07:55:33 +0000 In this study, by considering a space-based, -joint manipulator system as research object, a kinematic and a dynamic model are constructed and the system’s nonholonomic property is discussed. In light of the nonholonomic property unique to space-based systems, a path planning method is introduced to ensure that when an end-effector moves to the desired position, a floating base achieves the expected pose. The trajectories of the joints are first parameterized using sinusoidal polynomial functions, and cost functions are defined by the pose deviation of the base and the positional error of the end-effector. At this stage, the path planning problem is converted into a target optimization problem, where the target is a function of the joints. We then adopt a quantum genetic algorithm (QGA) to solve this objective optimization problem to attain the optimized trajectories of the joints and then execute nonholonomic path planning. To test the proposed method, we carried out a simulation on a six-degree-of-freedom (DOF) space-based manipulator system (SBMS). The results showed that, compared to traditional genetic optimization algorithms, the QGA converges more rapidly and has a more accurate output. Zhengcang Chen and Weijia Zhou Copyright © 2017 Zhengcang Chen and Weijia Zhou. All rights reserved. A Wearable Robotic Device Based on Twisted String Actuation for Rehabilitation and Assistive Applications Wed, 08 Mar 2017 00:00:00 +0000 The preliminary experimental study toward the implementation of an arm rehabilitation device based on a twisted string actuation module is presented. The actuation module is characterized by an integrated force sensor based on optoelectronic components. The adopted actuation system can be used for a wide set of robotic applications and is particularly suited for very compact, light-weight, and wearable robotic devices, such as wearable rehabilitation systems and exoskeletons. Thorough presentation and description of the proposed actuation module as well as the basic force sensor working principle are illustrated and discussed. A conceptual design of a wearable arm assistive system based on the proposed actuation module is presented. Moreover, the actuation module has been used in a simple assistive application, in which surface-electromyography signals are used to detect muscle activity of the user wearing the system and to regulate the support action provided to the user to reduce his effort, showing in this way the effectiveness of the approach. Mohssen Hosseini, Roberto Meattini, Gianluca Palli, and Claudio Melchiorri Copyright © 2017 Mohssen Hosseini et al. All rights reserved. A Crowd Avoidance Method Using Circular Avoidance Path for Robust Person Following Sun, 19 Feb 2017 00:00:00 +0000 A life-support service robot must avoid both static and dynamic obstacles for working in a real environment. Here, a static obstacle means an obstacle that does not move, and a dynamic obstacle is the one that moves. Assuming the robot is following a target person, we discuss how the robot avoids a crowd through which the target person passes and arrives at the target position. The purpose of this paper is to propose a crowd avoidance method that makes a robot to be able to avoid both static and dynamic obstacles. The method uses the surface points of the obstacles to form an avoidance region, and the robot moves along the edge of the region. We conducted experiments assuming various situations such that the robot was blocked, there was a wide gap in the crowd, or a person in the crowd yielded for the robot to pass through. As an experimental result, it was confirmed the robot could avoid the crowd even when the obstacles were aligned in an “inverted wedge” shape. Kohei Morishita, Yutaka Hiroi, and Akinori Ito Copyright © 2017 Kohei Morishita et al. All rights reserved. A Global Path Planning Algorithm Based on Bidirectional SVGA Thu, 02 Feb 2017 08:02:25 +0000 For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by ). This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning. Taizhi Lv, Chunxia Zhao, and Jiancheng Bao Copyright © 2017 Taizhi Lv et al. All rights reserved. Tracking a Subset of Skeleton Joints: An Effective Approach towards Complex Human Activity Recognition Tue, 17 Jan 2017 00:00:00 +0000 We present a robust algorithm for complex human activity recognition for natural human-robot interaction. The algorithm is based on tracking the position of selected joints in human skeleton. For any given activity, only a few skeleton joints are involved in performing the activity, so a subset of joints contributing the most towards the activity is selected. Our approach of tracking a subset of skeleton joints (instead of tracking the whole skeleton) is computationally efficient and provides better recognition accuracy. We have developed both manual and automatic approaches for the selection of these joints. The position of the selected joints is tracked for the duration of the activity and is used to construct feature vectors for each activity. Once the feature vectors have been constructed, we use a Support Vector Machines (SVM) multiclass classifier for training and testing the algorithm. The algorithm has been tested on a purposely built dataset of depth videos recorded using Kinect camera. The dataset consists of 250 videos of 10 different activities being performed by different users. Experimental results show classification accuracy of 83% when tracking all skeleton joints, 95% when using manual selection of subset joints, and 89% when using automatic selection of subset joints. Muhammad Latif Anjum, Stefano Rosa, and Basilio Bona Copyright © 2017 Muhammad Latif Anjum et al. All rights reserved. Corrigendum to “Mobile Robot Simultaneous Localization and Mapping Based on a Monocular Camera” Thu, 12 Jan 2017 07:51:54 +0000 Songmin Jia, Ke Wang, and Xiuzhi Li Copyright © 2017 Songmin Jia et al. All rights reserved. Keyframes Global Map Establishing Method for Robot Localization through Content-Based Image Matching Wed, 11 Jan 2017 00:00:00 +0000 Self-localization and mapping are important for indoor mobile robot. We report a robust algorithm for map building and subsequent localization especially suited for indoor floor-cleaning robots. Common methods, for example, SLAM, can easily be kidnapped by colliding or disturbed by similar objects. Therefore, keyframes global map establishing method for robot localization in multiple rooms and corridors is needed. Content-based image matching is the core of this method. It is designed for the situation, by establishing keyframes containing both floor and distorted wall images. Image distortion, caused by robot view angle and movement, is analyzed and deduced. And an image matching solution is presented, consisting of extraction of overlap regions of keyframes extraction and overlap region rebuild through subblocks matching. For improving accuracy, ceiling points detecting and mismatching subblocks checking methods are incorporated. This matching method can process environment video effectively. In experiments, less than 5% frames are extracted as keyframes to build global map, which have large space distance and overlap each other. Through this method, robot can localize itself by matching its real-time vision frames with our keyframes map. Even with many similar objects/background in the environment or kidnapping robot, robot localization is achieved with position RMSE <0.5 m. Tianyang Cao, Haoyuan Cai, Dongming Fang, Hui Huang, and Chang Liu Copyright © 2017 Tianyang Cao et al. All rights reserved. A Simple Outdoor Environment Obstacle Detection Method Based on Information Fusion of Depth and Infrared Sun, 04 Dec 2016 12:19:04 +0000 In allusion to the existing low recognition rate and robustness problem in obstacle detection; a simple but effective obstacle detection algorithm of information fusion in the depth and infrared is put forward. The scenario is segmented by the mean-shift algorithm and the pixel gradient of foreground is calculated. After pretreatment of edge detection and morphological operation, the depth information and infrared information are fused. The characteristics of depth map and infrared image in edge detection are used for the raised method, the false rate of detection is reduced, and detection precision is improved. Since the depth map and infrared image are not affected by natural sunlight, the influence on obstacle recognition due to the factors such as light intensity and shadow is effectively reduced and the robustness of the algorithm is also improved. Experiments indicate that the detection algorithm of information fusion can accurately identify the small obstacle in the view and the accuracy of obstacle recognition will not be affected by light. Hence, this method has great significance for mobile robot or intelligent vehicles on obstacle detection in outdoor environment. Yaguang Zhu, Baomin Yi, and Tong Guo Copyright © 2016 Yaguang Zhu et al. All rights reserved. Design of a New Nonlinear Stiffness Compliant Actuator and Its Error Compensation Method Sun, 30 Oct 2016 08:37:16 +0000 Compliant actuators are more advantageous than stiff actuators in some circumstances, for example, unstructured environment robots and rehabilitation robots. Compliant actuators are more adaptive and safe. Constant stiffness compliant actuators have some limitations in impedance and bandwidth. Variable stiffness actuators improve their performance owing to introducing an extra motor to tune the stiffness of the actuators. However, they also have some limitations such as the bulky structure and heavy weight. It was also found that there are some waste functions existing in the current variable stiffness actuators and that the fully decoupled position control and stiffness tune are not necessary, because there exist some regular phenomena during most circumstances of human interaction with the robots which are “low load, low stiffness and high load, high stiffness”. In this paper, a design method for nonlinear stiffness compliant actuator was proposed which performed the predefined deflection-torque trajectory of the regular phenomenon. A roller and a cantilever which has special curve profile constitute the basic mechanical structure of the nonlinear stiffness compliant actuators. An error compensation method was also proposed to analyze the stiffness of elastic structure. The simulation results proved that the proposed method was effective in designing a predefined nonlinear stiffness compliant actuator. Shaobin Lan and Zhibin Song Copyright © 2016 Shaobin Lan and Zhibin Song. All rights reserved. Design of Connectivity Preserving Flocking Using Control Lyapunov Function Sun, 16 Oct 2016 16:02:46 +0000 This paper investigates cooperative flocking control design with connectivity preserving mechanism. During flocking, interagent distance is measured to determine communication topology of the flocks. Then, cooperative flocking motion is built based on cooperative artificial potential field with connectivity preserving mechanism to achieve the common flocking objective. The flocking control input is then obtained by deriving cooperative artificial potential field using control Lyapunov function. As a result, we prove that our flocking protocol establishes group stabilization and the communication topology of multiagent flocking is always connected. Bayu Erfianto, Riyanto T. Bambang, Hilwadi Hindersah, and Intan Muchtadi-Alamsyah Copyright © 2016 Bayu Erfianto et al. All rights reserved. Review of Neurobiologically Based Mobile Robot Navigation System Research Performed Since 2000 Sun, 25 Sep 2016 09:32:07 +0000 In an attempt to better understand how the navigation part of the brain works and to possibly create smarter and more reliable navigation systems, many papers have been written in the field of biomimetic systems. This paper presents a literature survey of state-of-the-art research performed since the year 2000 on rodent neurobiological and neurophysiologically based navigation systems that incorporate models of spatial awareness and navigation brain cells. The main focus is to explore the functionality of the cognitive maps developed in these mobile robot systems with respect to route planning, as well as a discussion/analysis of the computational complexity required to scale these systems. Peter J. Zeno, Sarosh Patel, and Tarek M. Sobh Copyright © 2016 Peter J. Zeno et al. All rights reserved. Robot Obstacle Avoidance Learning Based on Mixture Models Wed, 07 Sep 2016 09:22:24 +0000 We briefly surveyed the existing obstacle avoidance algorithms; then a new obstacle avoidance learning framework based on learning from demonstration (LfD) is proposed. The main idea is to imitate the obstacle avoidance mechanism of human beings, in which humans learn to make a decision based on the sensor information obtained by interacting with environment. Firstly, we endow robots with obstacle avoidance experience by teaching them to avoid obstacles in different situations. In this process, a lot of data are collected as a training set; then, to encode the training set data, which is equivalent to extracting the constraints of the task, Gaussian mixture model (GMM) is used. Secondly, a smooth obstacle-free path is generated by Gaussian mixture regression (GMR). Thirdly, a metric of imitation performance is constructed to derive a proper control policy. The proposed framework shows excellent generalization performance, which means that the robots can fulfill obstacle avoidance task efficiently in a dynamic environment. More importantly, the framework allows learning a wide variety of skills, such as grasp and manipulation work, which makes it possible to build a robot with versatile functions. Finally, simulation experiments are conducted on a Turtlebot robot to verify the validity of our algorithms. Huiwen Zhang, Xiaoning Han, Mingliang Fu, and Weijia Zhou Copyright © 2016 Huiwen Zhang et al. All rights reserved. A Review on Compliant Joint Mechanisms for Lower Limb Exoskeletons Sun, 07 Aug 2016 09:26:17 +0000 Lower limb exoskeletons are experiencing a rapid development that may suggest a prompt introduction to the market. These devices have an inherent close interaction with the human body; therefore, it is necessary to ensure user’s safety and comfort. The first exoskeletal designs used to represent the human joints as simple revolute joints. This approximation introduces an axial misalignment issue, which generates uncontrollable internal forces. A mathematical description of the said misalignments is provided to better understand the concept and its consequences. This review will only focus on mechanisms aiming to comply with its user. Miguel A. Gálvez-Zúñiga and Alejandro Aceves-López Copyright © 2016 Miguel A. Gálvez-Zúñiga and Alejandro Aceves-López. All rights reserved. Research on Path Planning Method of Coal Mine Robot to Avoid Obstacle in Gas Distribution Area Wed, 03 Aug 2016 09:55:23 +0000 As the explosion-proof safety level of a coal mine robot has not yet reached the level of intrinsic safety “ia” and it cannot work in a dangerous gas distribution area, therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. In this paper, to avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed with consideration of gas concentration distributions. First, with consideration of gas distribution area and obstacles, MAKLINK method is adopted to describe the working environment network diagram of the coal mine robot. Second, the initial working paths for the coal mine robot are obtained based on Dijkstra algorithm, and then the global optimal working path for the coal mine robot is obtained based on ant colony algorithm. Lastly, experiments are conducted in a roadway after an accident, and results by different path planning methods are compared, which verified the effectiveness of the proposed path planning method. Ruiqing Mao and Xiliang Ma Copyright © 2016 Ruiqing Mao and Xiliang Ma. All rights reserved. Bioinspired Knee Joint for a Power-Assist Suit Thu, 14 Jul 2016 13:25:47 +0000 Movement of the knee joint of a human includes rolling and sliding. There also exist rotations in the frontal and horizontal planes. To assist the standing movement of a human, we developed a bioinspired knee joint and torque adjustment mechanism. We evaluated the motion, torque characteristics, and stress of the developed mechanism. This joint allows deep flexion of the knee with small resistance for both the user and the device. In addition, in spite of 33% error in deep flexion, the measured torque over less than 120 degrees fits the designed torque curve. We conducted evaluation tests for a human subject. The electromyogram (EMG) of musculus rectus femoris was measured during standing with or without the assistance. The result shows 30% and 63% reduction with the assistance from 100-degree and 80-degree knee angles, respectively. In addition, the proposed device reduced up to 80% of stress in the frontal plane during standing. Takehito Kikuchi, Kohei Sakai, and Isao Abe Copyright © 2016 Takehito Kikuchi et al. All rights reserved. Galloping Trajectory Generation of a Legged Transport Robot Based on Energy Consumption Optimization Tue, 05 Jul 2016 11:53:27 +0000 Legged walking robots have very strong operation ability in the complex surface and they are very suitable for transportation of tools, materials, and equipment in unstructured environment. Aiming at the problems of energy consumption of legged transport robot during the fast moving, a method of galloping trajectory planning based on energy consumption optimization is proposed. By establishing transition angle polynomials of flight phase, lift-off phase, and stance phase and constraint condition between each state phase, the locomotion equations of the ellipse trajectory are derived. The transition angle of each state phase is introduced into the system energy consumption equations, and the energy optimization index based on transition angles is established. Inverse kinematics solution and trajectory planning in one gait cycle are applied to genetic algorithm process to solve the nonlinear programming problem. The results show that the optimized distribution of transition angles of state phases is more reasonable, and joint torques and system energy consumption are reduced effectively. Thus, the method mentioned above has a great significance to realize fast operation outdoors of transport robot. Yaguang Zhu and Tong Guo Copyright © 2016 Yaguang Zhu and Tong Guo. All rights reserved. Kinematics and Dynamics of a Tensegrity-Based Water Wave Energy Harvester Tue, 14 Jun 2016 08:41:21 +0000 A tensegrity-based water wave energy harvester is proposed. The direct and inverse kinematic problems are investigated by using a geometric method. Afterwards, the singularities and workspaces are discussed. Then, the Lagrangian method was used to develop the dynamic model considering the interaction between the harvester and water waves. The results indicate that the proposed harvester allows harvesting 13.59% more energy than a conventional heaving system. Therefore, tensegrity systems can be viewed as one alternative solution to conventional water wave energy harvesting systems. Min Lin, Tuanjie Li, and Zhifei Ji Copyright © 2016 Min Lin et al. All rights reserved.