A demonstration and comparative analysis of haptic performance using a Gough-Stewart platform as a wearable haptic feedback device

In many hazardous work environments, contact tasks ranging from manufacturing to disassembly to emergency response are performed by industrial manipulators. Due to the hazardous and complex nature of these environments, teleoperation is often employed. When such is the case, the operator is left to interpret a large amount of data during task completion due to the complexity of modern robotic systems and the possible complexity of the tasks. This information is usually processed visually but can lead to sensory overload. To mitigate this, the information processing can also be distributed through other modes of sensory such as auditory or haptic. The University of Texas at Austin's TeMoto hands-free interface reduces the burden on the operator of commanding remote systems by enabling the use of gestural and verbal commands to complete a range of tasks, but the removal of a mechanical interactive device from the operator interface complicates the inclusion of haptic feedback. In this work, a standalone Gough-Stewart platform previously configured as a wearable haptic feedback device for the Nuclear and Applied Robotics Group at the University of Texas at Austin provides real-time haptic feedback to the unconstrained hand(s) of the operator. In doing so, this haptic interface can be employed with the intent of enhancing situational awareness and minimizing operator stress by imparting forces and torques to the user based on those imparted on the end-effector of the industrial manipulator. While multiple technical issues and human factor issues must be addressed, this effort focuses on integrating the system and evaluating its performance for various industrial manipulator designs and sensor modalities. After testing various digital signal processing techniques, functionality was demonstrated among one series-elastic and two rigid industrial manipulators, each with different force/torque data acquisition characteristics and a comparative analysis in haptic performance was performed. Furthermore, it was demonstrated with the TeMoto hands-free teleoperation system. Overall, the demonstrations and experiments performed in this work prove the system to be a viable, hardware agnostic means of haptic feedback and a strong basis for future effortsMechanical Engineerin

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

Overtwisting and Coiling Highly Enhances Strain Generation of Twisted String Actuators

Twisted string actuators (TSAs) have exhibited great promise in robotic applications by generating high translational force with low input torque. To further facilitate their robotic applications, it is strongly desirable but challenging to enhance their consistent strain generation while maintaining compliance. Existing studies predominantly considered overtwisting and coiling after the regular twisting stage to be undesirable non-uniform and unpredictable knots, entanglements, and coils formed to create an unstable and failure-prone structure. Overtwisting would work well for TSAs when uniform coils can be consistently formed. In this study, we realize uniform and consistent coil formation in overtwisted TSAs, which greatly increases their strain. Furthermore, we investigate methods for enabling uniform coil formation upon overtwisting the strings in a TSA and present a procedure to systematically "train" the strings. To the authors' best knowledge, this is the first study to experimentally investigate overtwisting for TSAs with different stiffnesses and realize consistent uniform coil formation. Ultra-high molecular-weight polyethylene (UHMWPE) strings form the stiff TSAs whereas compliant TSAs are realized with stretchable and conductive supercoiled polymer (SCP) strings. The strain, force, velocity, and torque of each overtwisted TSA was studied. Overtwisting and coiling resulted in approximately 70% strain in stiff TSAs and approximately 60% strain in compliant TSAs. This is more than twice the strain achieved through regular twisting. Lastly, the overtwisted TSA was successfully demonstrated in a robotic bicep

Inertial learning and haptics for legged robot state estimation in visually challenging environments

Legged robots have enormous potential to automate dangerous or dirty jobs because they are capable of traversing a wide range of difficult terrains such as up stairs or through mud. However, a significant challenge preventing widespread deployment of legged robots is a lack of robust state estimation, particularly in visually challenging conditions such as darkness or smoke. In this thesis, I address these challenges by exploiting proprioceptive sensing from inertial, kinematic and haptic sensors to provide more accurate state estimation when visual sensors fail. Four different methods are presented, including the use of haptic localisation, terrain semantic localisation, learned inertial odometry, and deep learning to infer the evolution of IMU biases. The first approach exploits haptics as a source of proprioceptive localisation by comparing geometric information to a prior map. The second method expands on this concept by fusing both semantic and geometric information, allowing for accurate localisation on diverse terrain. Next, I combine new techniques in inertial learning with classical IMU integration and legged robot kinematics to provide more robust state estimation. This is further developed to use only IMU data, for an application entirely different from robotics: 3D reconstruction of bone with a handheld ultrasound scanner. Finally, I present the novel idea of using deep learning to infer the evolution of IMU biases, improving state estimation in exteroceptive systems where vision fails. Legged robots have the potential to benefit society by automating dangerous, dull, or dirty jobs and by assisting first responders in emergency situations. However, there remain many unsolved challenges to the real-world deployment of legged robots, including accurate state estimation in vision-denied environments. The work presented in this thesis takes a step towards solving these challenges and enabling the deployment of legged robots in a variety of applications

Master of Science

thesisIncreased demand for powered wheelchairs and their inherent mobility limitations have prompted the development of omnidirectional wheelchairs. These wheelchairs provide improved mobility in confined spaces, but can be more difficult to control and impact the ability of the user to embody the wheelchair. We hypothesize that control and embodiment of omnidirectional wheelchairs can be improved by providing intuitive control with three degree of freedom (3-DOF) haptic feedback that directly corresponds to the degrees of freedom of an omnidirectional wheelchair. This thesis introduces a novel 3-DOF Haptic Joystick designed for the purpose of controlling omnidirectional wheelchairs. When coupled with range finders, it is able to provide the user with feedback that improves the operator's awareness of the area surrounding the vehicle and assists the driver in obstacle avoidance. The haptic controller design and a stability analysis of the coupled wheelchair joystick systems are presented. Experimental results from the coupled systems validate the ability of the controller to influence the trajectory of the wheelchair and assist in obstacle avoidance

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

High-performance series elastic actuation

textMobile legged robots have the potential to restructure many aspects of our lives in the near future. Whether for applications in household care, entertainment, or disaster response, these systems depend on high-performance actuators to improve their basic capabilities. The work presented here focuses on developing new high-performance actuators, specifically series elastic actuators, to address this need. We adopt a system-wide optimization approach, dealing with factors which influence performance at the levels of mechanical design, electrical system design, and control. Using this approach and based on a set of performance metrics, we produce an actuator, the UT-SEA, which achieves leading empirical results in terms of power-to-weight, force control, size, and system efficiency. We also develop general high-performance control techniques for both force- and position-controlled actuators, some of which were adopted for use on NASA-JSC's Valkyrie Humanoid robot and were used during DARPA's DRC Trials 2013 robotics competition.Electrical and Computer Engineerin