Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery

© 2016 IEEE. An improved human-robot collaborative control scheme is proposed in a teleoperated minimally invasive surgery scenario, based on a hierarchical operational space formulation of a seven-degree-of-freedom redundant robot. Redundancy is exploited to guarantee a remote center of motion (RCM) constraint and to provide a compliant behavior for the medical staff. Based on the implemented hierarchical control framework, an RCM constraint and a safe constraint are applied to the null-space motion to achieve the surgical tasks with human-robot interaction. Due to the physical interactions, safety and accuracy of the surgery may be affected. The control framework integrates an adaptive compensator to enhance the accuracy of the surgical tip and to maintain the RCM constraint in a decoupled way avoiding any physical interactions. The system performance is verified on a patient phantom. Compared with the methods proposed in the literature, results show that the accuracy of both the RCM constraint and the surgical tip is improved. The compliant swivel motion of the robot arm is also constrained in a defined area, and the interaction force on the abdominal wall becomes smaller

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Design and implementation of robotic devices for physical therapy of distal upper extremity

According to statistics of World Health Organization, hand injuries count for 1/3 of all injuries with more than one million emergency cases annually. Physical rehabilitation accounts for most of the recovery experienced by patients suffering from hand injury. Robotic devices decrease the cost of therapy while providing repetitive exercises with quantitative measurements. In this study, we present the design and implementation of two robotic devices for hand therapy. After kinematic type selection ensuring safety, ergonomics and adjustability; both of the devices are optimally dimensioned to achieve best kinematic and dynamic performance. The primary use for the first device is to assist flexion/extension motions of a finger within its full range, in a natural and coordinated manner, while keeping the tendon tension within acceptable limits to avoid rupture of the suture. The second device is designed for forearm/wrist and grasp therapy of a neurologically injured human arm and hand. Emphasizing the importance of coordinated movements of the wrist and the hand while performing activities of daily living (ADL) tasks, the device possesses 3 degrees of freedom and is designed to assist abduction/adduction and palmar/dorsal flexion of the wrist or pronation/supination of the forearm, concurrently with the grasping and releasing movements of the hand. Thanks to its modular, interchangeable end effectors, the device supports ADL exercises. Both devices are built and experimentally characterized. Human subject experiments and usability tests have been conducted for the devices and the efficacy of devices to deliver desired wrist and hand therapies have been demonstrated

Cognitive Reasoning for Compliant Robot Manipulation

Physically compliant contact is a major element for many tasks in everyday environments. A universal service robot that is utilized to collect leaves in a park, polish a workpiece, or clean solar panels requires the cognition and manipulation capabilities to facilitate such compliant interaction. Evolution equipped humans with advanced mental abilities to envision physical contact situations and their resulting outcome, dexterous motor skills to perform the actions accordingly, as well as a sense of quality to rate the outcome of the task. In order to achieve human-like performance, a robot must provide the necessary methods to represent, plan, execute, and interpret compliant manipulation tasks. This dissertation covers those four steps of reasoning in the concept of intelligent physical compliance. The contributions advance the capabilities of service robots by combining artificial intelligence reasoning methods and control strategies for compliant manipulation. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. Novel representations are derived to describe the properties of physical interaction. Special attention is given to wiping tasks which are predominant in everyday environments. It is investigated how symbolic task descriptions can be translated into meaningful robot commands. A particle distribution model is used to plan goal-oriented wiping actions and predict the quality according to the anticipated result. The planned tool motions are converted into the joint space of the humanoid robot Rollin' Justin to perform the tasks in the real world. In order to execute the motions in a physically compliant fashion, a hierarchical whole-body impedance controller is integrated into the framework. The controller is automatically parameterized with respect to the requirements of the particular task. Haptic feedback is utilized to infer contact and interpret the performance semantically. Finally, the robot is able to compensate for possible disturbances as it plans additional recovery motions while effectively closing the cognitive control loop. Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment. This application demonstrates the far-reaching impact of the proposed approach and the associated opportunities that emerge with the availability of cognition-enabled service robots

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Biomimetic Manipulator Control Design for Bimanual Tasks in the Natural Environment

As robots become more prolific in the human environment, it is important that safe operational procedures are introduced at the same time; typical robot control methods are often very stiff to maintain good positional tracking, but this makes contact (purposeful or accidental) with the robot dangerous. In addition, if robots are to work cooperatively with humans, natural interaction between agents will make tasks easier to perform with less effort and learning time. Stability of the robot is particularly important in this situation, especially as outside forces are likely to affect the manipulator when in a close working environment; for example, a user leaning on the arm, or task-related disturbance at the end-effector. Recent research has discovered the mechanisms of how humans adapt the applied force and impedance during tasks. Studies have been performed to apply this adaptation to robots, with promising results showing an improvement in tracking and effort reduction over other adaptive methods. The basic algorithm is straightforward to implement, and allows the robot to be compliant most of the time and only stiff when required by the task. This allows the robot to work in an environment close to humans, but also suggests that it could create a natural work interaction with a human. In addition, no force sensor is needed, which means the algorithm can be implemented on almost any robot. This work develops a stable control method for bimanual robot tasks, which could also be applied to robot-human interactive tasks. A dynamic model of the Baxter robot is created and verified, which is then used for controller simulations. The biomimetic control algorithm forms the basis of the controller, which is developed into a hybrid control system to improve both task-space and joint-space control when the manipulator is disturbed in the natural environment. Fuzzy systems are implemented to remove the need for repetitive and time consuming parameter tuning, and also allows the controller to actively improve performance during the task. Experimental simulations are performed, and demonstrate how the hybrid task/joint-space controller performs better than either of the component parts under the same conditions. The fuzzy tuning method is then applied to the hybrid controller, which is shown to slightly improve performance as well as automating the gain tuning process. In summary, a novel biomimetic hybrid controller is presented, with a fuzzy mechanism to avoid the gain tuning process, finalised with a demonstration of task-suitability in a bimanual-type situation.EPSR

Acquisition and distribution of synergistic reactive control skills

Learning from demonstration is an afficient way to attain a new skill. In the context of autonomous robots, using a demonstration to teach a robot accelerates the robot learning process significantly. It helps to identify feasible solutions as starting points for future exploration or to avoid actions that lead to failure. But the acquisition of pertinent observationa is predicated on first segmenting the data into meaningful sequences. These segments form the basis for learning models capable of recognising future actions and reconstructing the motion to control a robot. Furthermore, learning algorithms for generative models are generally not tuned to produce stable trajectories and suffer from parameter redundancy for high degree of freedom robots This thesis addresses these issues by firstly investigating algorithms, based on dynamic programming and mixture models, for segmentation sensitivity and recognition accuracy on human motion capture data sets of repetitive and categorical motion classes. A stability analysis of the non-linear dynamical systems derived from the resultant mixture model representations aims to ensure that any trajectories converge to the intended target motion as observed in the demonstrations. Finally, these concepts are extended to humanoid robots by deploying a factor analyser for each mixture model component and coordinating the structure into a low dimensional representation of the demonstrated trajectories. This representation can be constructed as a correspondence map is learned between the demonstrator and robot for joint space actions. Applying these algorithms for demonstrating movement skills to robot is a further step towards autonomous incremental robot learning

Applied Mathematics to Mechanisms and Machines

This book brings together all 16 articles published in the Special Issue "Applied Mathematics to Mechanisms and Machines" of the MDPI Mathematics journal, in the section “Engineering Mathematics”. The subject matter covered by these works is varied, but they all have mechanisms as the object of study and mathematics as the basis of the methodology used. In fact, the synthesis, design and optimization of mechanisms, robotics, automotives, maintenance 4.0, machine vibrations, control, biomechanics and medical devices are among the topics covered in this book. This volume may be of interest to all who work in the field of mechanism and machine science and we hope that it will contribute to the development of both mechanical engineering and applied mathematics

Microfactory concept with bilevel modularity

There has been an increasing demand for miniaturization of products in the last decades. As a result of that, miniaturization and micro systems have become an important topic of research. As the technologies of micro manufacturing improve and are gradually started to be used, new devices have started to emerge in to the market. However, the miniaturization of the products is not paralleled to the sizes of the equipment used for their production. The conventional equipment for production of microparts is comparable in size and energy consumption to their counterparts in the macro world. The miniaturization of products and parts is slowly paving the way to the miniaturization of the production equipment and facilities, enabling efficient use of energy for production, improvement in material resource utilization and high speed and precision which in turn will lead to an increase in the amount of products produced more precisely. These led to the introduction of the microfactory concept which involves the miniaturization of the conventional production systems with all their features trying to facilitate the advantages that are given above. The aim of this thesis is to develop a module structure for production and assembly which can be cascaded with other modules in order to form a layout for the production of a specific product. The layout can also be changed in order to configure the microfactory for the production of another product. This feature brings flexibility to the system in the sense of product design and customization of products. Each module having its own control system, is able to perform its duty with the equipment placed into it. In order to form different layouts using the modules to build up a complete production chain, each module is equipped with necessary interface modules for the interaction and communication with the other process modules. In this work, the concept of process oriented modules with bilevel modularity is introduced for the development of microfactory modules. The first phase of the project is defined to be the realization of an assembly module and forms the content of this thesis. The assembly module contains parallel kinematics robots as manipulators which performs the assigned operations. One of the most important part here is to configure the structure of the module (control system/interface and communication units, etc.) which will in the future enable the easy integration of different process modules in order to form a whole microfactory which will have the ability to perform all phases of production necessary for the manufacturing of a product. The assembly module is a miniaturized version of the conventional factories (i.e. an assembly line) in such a way that the existing industrial standards are imitated within the modules of the microfactory. So that one who is familiar with the conventional systems can also be familiar with the construction of the realized miniature system and can easily setup the system according to the needs of the application. Thus, this is an important step towards the come in to use of the miniaturized production units in the industry. In order to achieve that kind of structure, necessary control hardware and software architecture are implemented which allows easy configuration of the system according to the processes. The modularity and reconfigurability in the software structure also have significant importance besides the modularity of the mechanical structure. The miniaturization process for the assembly cell includes the miniaturization of the parallel manipulators, transportation system in between the assembly nodes or in between different modules and the control system hardware. Visual sensor utilization for the visual feedback is enabled for the assembly process at the necessary nodes. The assembly module is developed and experiments are realized in order to test the performance of the module

Proceedings of the NASA Conference on Space Telerobotics, volume 4

Papers presented at the NASA Conference on Space Telerobotics are compiled. The theme of the conference was man-machine collaboration in space. The conference provided a forum for researchers and engineers to exchange ideas on the research and development required for the application of telerobotic technology to the space systems planned for the 1990's and beyond. Volume 4 contains papers related to the following subject areas: manipulator control; telemanipulation; flight experiments (systems and simulators); sensor-based planning; robot kinematics, dynamics, and control; robot task planning and assembly; and research activities at the NASA Langley Research Center