International Science Index
Laser Registration and Supervisory Control of neuroArm Robotic Surgical System
This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.
Representations of Childcare Robots as a Controversial Issue
This paper interrogates online representations of robot companions for children, including promotional material by manufacturers, media articles and technology blogs. The significance of the study lies in its contribution to understanding attitudes to robots. The prospect of childcare robots is particularly controversial ethically, and is associated with emotive arguments. The sampled material is restricted to relatively recent posts (the past three years) though the analysis identifies both continuous and changing themes across the past decade. The method extrapolates social representations theory towards examining the ways in which information about robotic products is provided for the general public. Implications for social acceptance of robot companions for the home and robot ethics are considered.
Hand Controlled Mobile Robot Applied in Virtual Environment
By the development of IT systems, human-computer interaction is also developing even faster and newer communication methods become available in human-machine interaction. In this article, the application of a hand gesture controlled human-computer interface is being introduced through the example of a mobile robot. The control of the mobile robot is implemented in a realistic virtual environment that is advantageous regarding the aspect of different tests, parallel examinations, so the purchase of expensive equipment is unnecessary. The usability of the implemented hand gesture control has been evaluated by test subjects. According to the opinion of the testing subjects, the system can be well used, and its application would be recommended on other application fields too.
Distributed Coverage Control by Robot Networks in Unknown Environments Using a Modified EM Algorithm
In this paper, we study a distributed control algorithm
for the problem of unknown area coverage by a network of robots.
The coverage objective is to locate a set of targets in the area and
to minimize the robots’ energy consumption. The robots have no
prior knowledge about the location and also about the number of the
targets in the area. One efficient approach that can be used to relax
the robots’ lack of knowledge is to incorporate an auxiliary learning
algorithm into the control scheme. A learning algorithm actually
allows the robots to explore and study the unknown environment
and to eventually overcome their lack of knowledge. The control
algorithm itself is modeled based on game theory where the network
of the robots use their collective information to play a non-cooperative
potential game. The algorithm is tested via simulations to verify its
performance and adaptability.
A Robotic Cube to Preschool Children for Acquiring the Mathematical and Colours Concepts
This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.
Terrain Classification for Ground Robots Based on Acoustic Features
The motivation of our work is to detect different
terrain types traversed by a robot based on acoustic data from the
robot-terrain interaction. Different acoustic features and classifiers
were investigated, such as Mel-frequency cepstral coefficient and
Gamma-tone frequency cepstral coefficient for the feature extraction,
and Gaussian mixture model and Feed forward neural network for the
classification. We analyze the system’s performance by comparing
our proposed techniques with some other features surveyed from
distinct related works. We achieve precision and recall values between
87% and 100% per class, and an average accuracy at 95.2%. We also
study the effect of varying audio chunk size in the application phase
of the models and find only a mild impact on performance.
Virtual 3D Environments for Image-Based Navigation Algorithms
This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.
The Use of the Limit Cycles of Dynamic Systems for Formation of Program Trajectories of Points Feet of the Anthropomorphous Robot
The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.
Investigating Breakdowns in Human Robot Interaction: A Conversation Analysis Guided Single Case Study of a Human-Robot Communication in a Museum Environment
In a single case study, we show how a conversation analysis (CA) approach can shed light onto the sequential unfolding of human-robot interaction. Relying on video data, we are able to show that CA allows us to investigate the respective turn-taking systems of humans and a NAO robot in their dialogical dynamics, thus pointing out relevant differences. Our fine grained video analysis points out occurring breakdowns and their overcoming, when humans and a NAO-robot engage in a multimodally uttered multi-party communication during a sports guessing game. Our findings suggest that interdisciplinary work opens up the opportunity to gain new insights into the challenging issues of human robot communication in order to provide resources for developing mechanisms that enable complex human-robot interaction (HRI).
Metal Ship and Robotic Car: A Hands-On Activity to Develop Scientific and Engineering Skills for High School Students
Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.
Autonomic Sonar Sensor Fault Manager for Mobile Robots
NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.
Sampled-Data Model Predictive Tracking Control for Mobile Robot
In this paper, a sampled-data model predictive tracking
control method is presented for mobile robots which is modeled as
constrained continuous-time linear parameter varying (LPV) systems.
The presented sampled-data predictive controller is designed by linear
matrix inequality approach. Based on the input delay approach, a
controller design condition is derived by constructing a new Lyapunov
function. Finally, a numerical example is given to demonstrate the
effectiveness of the presented method.
Electromyography Pattern Classification with Laplacian Eigenmaps in Human Running
Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.
MAGNI Dynamics: A Vision-Based Kinematic and Dynamic Upper-Limb Model for Intelligent Robotic Rehabilitation
This paper presents a home-based robot-rehabilitation
instrument, called ”MAGNI Dynamics”, that utilized a vision-based
kinematic/dynamic module and an adaptive haptic feedback
controller. The system is expected to provide personalized
rehabilitation by adjusting its resistive and supportive behavior
according to a fuzzy intelligence controller that acts as an inference
system, which correlates the user’s performance to different stiffness
factors. The vision module uses the Kinect’s skeletal tracking to
monitor the user’s effort in an unobtrusive and safe way, by estimating
the torque that affects the user’s arm. The system’s torque estimations
are justified by capturing electromyographic data from primitive
hand motions (Shoulder Abduction and Shoulder Forward Flexion).
Moreover, we present and analyze how the Barrett WAM generates
a force-field with a haptic controller to support or challenge the
users. Experiments show that by shifting the proportional value,
that corresponds to different stiffness factors of the haptic path, can
potentially help the user to improve his/her motor skills. Finally,
potential areas for future research are discussed, that address how
a rehabilitation robotic framework may include multisensing data, to
improve the user’s recovery process.
Fall Avoidance Control of Wheeled Inverted Pendulum Type Robotic Wheelchair While Climbing Stairs
The wheelchair is the major means of transport for
physically disabled people. However, it cannot overcome architectural
barriers such as curbs and stairs. In this paper, the authors proposed
a method to avoid falling down of a wheeled inverted pendulum type
robotic wheelchair for climbing stairs. The problem of this system
is that the feedback gain of the wheels cannot be set high due to
modeling errors and gear backlash, which results in the movement
of wheels. Therefore, the wheels slide down the stairs or collide with
the side of the stairs, and finally the wheelchair falls down. To avoid
falling down, the authors proposed a slider control strategy based on
skyhook model in order to decrease the movement of wheels, and a
rotary link control strategy based on the staircase dimensions in order
to avoid collision or slide down. The effectiveness of the proposed
fall avoidance control strategy was validated by ODE simulations and
the prototype wheelchair.
Quantifying Key Factors Affecting Leagile Manufacturing System
In today’s market, striving hard has become necessary for the industries to survive due to the intense competition and globalization. In earlier days, there were few sellers and limited numbers of buyers, so customers were having fewer options to buy the product. But today, the market is highly competitive and volatile. Industries are focusing on robotics, advance manufacturing methods like AJM (Abrasive Jet Machining), EDM (Electric Discharge Machining), ECM (Electrochemical Machining) etc., CAD/CAM, CAE to make quality products and market them in shortest possible time. Leagile manufacturing system is ensuring best available solution at minimum cost to meet the market demand. This paper tries to assimilate the concept of Leagile manufacturing system in today’s scenario and evaluating key factors affecting Leagile manufacturing using digraph technique.
Multipurpose Agricultural Robot Platform: Conceptual Design of Control System Software for Autonomous Driving and Agricultural Operations Using Programmable Logic Controller
This paper discusses about the conceptual design and development of the control system software using Programmable logic controller (PLC) for autonomous driving and agricultural operations of Multipurpose Agricultural Robot Platform (MARP). Based on given initial conditions by field analysis and desired agricultural operations, the structural design development of MARP is done using modelling and analysis tool. PLC, being robust and easy to use, has been used to design the autonomous control system of robot platform for desired parameters. The robot is capable of performing autonomous driving and three automatic agricultural operations, viz. hilling, mulching, and sowing of seeds in the respective order. The input received from various sensors on the field is later transmitted to the controller via ZigBee network to make the changes in the control program to get desired field output. The research is conducted to provide assistance to farmers by reducing labor hours for agricultural activities by implementing automation. This study will provide an alternative to the existing systems with machineries attached behind tractors and rigorous manual operations on agricultural field at effective cost.
Application of Robotics to Assemble a Used Fuel Container in the Canadian Used Fuel Packing Plant
The newest Canadian Used Fuel Container (UFC)- (called also “Mark II”) modifies the design approach for its Assembly Robotic Cell (ARC) in the Canadian Used (Nuclear) Fuel Packing Plant (UFPP). Some of the robotic design solutions are presented in this paper. The design indicates that robots and manipulators are expected to be used in the Canadian UFPP. As normally, the UFPP design will incorporate redundancy of all equipment to allow expedient recovery from any postulated upset conditions. Overall, this paper suggests that robot usage will have a significant positive impact on nuclear safety, quality, productivity, and reliability.
Control Strategies for a Robot for Interaction with Children with Autism Spectrum Disorder
Socially assistive robotic has become increasingly active and it is present in therapies of people affected for several neurobehavioral conditions, such as Autism Spectrum Disorder (ASD). In fact, robots have played a significant role for positive interaction with children with ASD, by stimulating their social and cognitive skills. This work introduces a mobile socially-assistive robot, which was built for interaction with children with ASD, using non-linear control techniques for this interaction.
Study on Robot Trajectory Planning by Robot End-Effector Using Dual Curvature Theory of the Ruled Surface
This paper presents the method of trajectory planning by the robot end-effector which accounts for more accurate and smooth differential geometry of the ruled surface generated by tool line fixed with end-effector based on the methods of curvature theory of ruled surface and the dual curvature theory, and focuses on the underlying relation to unite them for enhancing the efficiency for trajectory planning. Robot motion can be represented as motion properties of the ruled surface generated by trajectory of the Tool Center Point (TCP). The linear and angular properties of the six degree-of-freedom motion of end-effector are computed using the explicit formulas and functions from curvature theory and dual curvature theory. This paper explains the complete dualization of ruled surface and shows that the linear and angular motion applied using the method of dual curvature theory is more accurate and less complex.
A Comparison of Inverse Simulation-Based Fault Detection in a Simple Robotic Rover with a Traditional Model-Based Method
Robotic rovers which are designed to work in
extra-terrestrial environments present a unique challenge in terms
of the reliability and availability of systems throughout the mission.
Should some fault occur, with the nearest human potentially millions
of kilometres away, detection and identification of the fault must
be performed solely by the robot and its subsystems. Faults in
the system sensors are relatively straightforward to detect, through
the residuals produced by comparison of the system output with
that of a simple model. However, faults in the input, that is, the
actuators of the system, are harder to detect. A step change in
the input signal, caused potentially by the loss of an actuator,
can propagate through the system, resulting in complex residuals
in multiple outputs. These residuals can be difficult to isolate or
distinguish from residuals caused by environmental disturbances.
While a more complex fault detection method or additional sensors
could be used to solve these issues, an alternative is presented here.
Using inverse simulation (InvSim), the inputs and outputs of the
mathematical model of the rover system are reversed. Thus, for a
desired trajectory, the corresponding actuator inputs are obtained.
A step fault near the input then manifests itself as a step change
in the residual between the system inputs and the input trajectory
obtained through inverse simulation. This approach avoids the need
for additional hardware on a mass- and power-critical system such
as the rover. The InvSim fault detection method is applied to a
simple four-wheeled rover in simulation. Additive system faults and
an external disturbance force and are applied to the vehicle in turn,
such that the dynamic response and sensor output of the rover
are impacted. Basic model-based fault detection is then employed
to provide output residuals which may be analysed to provide
information on the fault/disturbance. InvSim-based fault detection
is then employed, similarly providing input residuals which provide
further information on the fault/disturbance. The input residuals are
shown to provide clearer information on the location and magnitude
of an input fault than the output residuals. Additionally, they can
allow faults to be more clearly discriminated from environmental
Genetic Algorithm Based Deep Learning Parameters Tuning for Robot Object Recognition and Grasping
This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.
Robot Navigation and Localization Based on the Rat’s Brain Signals
The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.
Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis
This study presents a framework for development of a
new generation of therapy robots that can interact with users by
monitoring their physiological and mental states. Here, we focused
on one of the controversial methods of therapy, hypnotherapy.
Hypnosis has shown to be useful in treatment of many clinical
conditions. But, even for healthy people, it can be used as an
effective technique for relaxation or enhancement of memory and
concentration. Our aim is to develop a robot that collects information
about user’s mental and physical states using electroencephalogram
(EEG) and electromyography (EMG) signals and performs costeffective
hypnosis at the comfort of user’s house. The presented
framework consists of three main steps: (1) Find the EEG-correlates
of mind state before, during, and after hypnosis and establish a
cognitive model for state changes, (2) Develop a system that can
track the changes in EEG and EMG activities in real time and
determines if the user is ready for suggestion, and (3) Implement our
system in a humanoid robot that will talk and conduct hypnosis on
users based on their mental states. This paper presents a pilot study in
regard to the first stage, detection of EEG and EMG features during
H-Infinity and RST Position Controllers of Rotary Traveling Wave Ultrasonic Motor
Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.
Neuron-Based Control Mechanisms for a Robotic Arm and Hand
A robotic arm and hand controlled by simulated
neurons is presented. The robot makes use of a biological neuron
simulator using a point neural model. The neurons and synapses are
organised to create a finite state automaton including neural inputs
from sensors, and outputs to effectors. The robot performs a simple
pick-and-place task. This work is a proof of concept study for a
longer term approach. It is hoped that further work will lead to
more effective and flexible robots. As another benefit, it is hoped that
further work will also lead to a better understanding of human and
other animal neural processing, particularly for physical motion. This
is a multidisciplinary approach combining cognitive neuroscience,
robotics, and psychology.
Technological Development and Implementation of a Robotic Arm Motioned by Programmable Logic Controller
The robot manipulator is an equipment that stands out for two reasons: Firstly because of its characteristics of movement and reprogramming, resembling the arm; secondly, by adding several areas of knowledge of science and engineering. The present work shows the development of the prototype of a robotic manipulator driven by a Programmable Logic Controller (PLC), having two degrees of freedom, which allows the movement and displacement of mechanical parts, tools, and objects in general of small size, through an electronic system. The aim is to study direct and inverse kinematics of the robotic manipulator to describe the translation and rotation between two adjacent links of the robot through the Denavit-Hartenberg parameters. Currently, due to the many resources that microcomputer systems offer us, robotics is going through a period of continuous growth that will allow, in a short time, the development of intelligent robots with the capacity to perform operations that require flexibility, speed and precision.
Simulation-Based Diversity Management in Human-Robot Collaborative Scenarios
In this paper, the influence of diversity-related factors on the design of collaborative scenarios is analysed. Based on the evaluation, a framework for simulating human-robot-collaboration is presented that considers both human factors as well as the overall system performance. The implementation of the model is shown on a real-life scenario from industry and validated in terms of traceability, safety and physical limitations. By comparing scenarios that consider diversity with those only meeting system performance, an overall understanding of individually adapted human-robot-collaborative workspaces is reached. A diversity-related guideline for human-robot-collaborations provides a summary of the research and aids in optimizing future applications. Finally, limitations and future amendments of the model are discussed.
Analysis of Stress and Strain in Head Based Control of Cooperative Robots through Tetraplegics
Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.
Retraction Free Motion Approach and Its Application in Automated Robotic Edge Finishing and Inspection Processes
In this paper, a motion generation algorithm for a six Degrees of Freedom (DoF) robotic hand in a static environment is presented. The purpose of developing this method is to be used in the path generation of the end-effector for edge finishing and inspection processes by utilizing the CAD model of the considered workpiece. Nonetheless, the proposed algorithm may be extended to be applicable for other similar manufacturing processes. A software package programmed in the application programming interface (API) of SolidWorks generates tool path data for the robot. The proposed method significantly simplifies the given problem, resulting in a reduction in the CPU time needed to generate the path, and offers an efficient overall solution. The ABB IRB2000 robot is chosen for executing the generated tool path.