Developing Intuitive, Closed-Loop, Teleoperative Control of Continuum Robotic Systems

This thesis presents a series of related new results in the area of continuum robot teleoperation and control. A new nonlinear control strategy for the teleoperation of extensible continuum robots is described. Previous attempts at controlling continuum robots have proven difficult due to the complexity of their system dynamics. Taking advantage of a previously developed dynamic model for a three-section, planar, continuum manipulator, we present an adaptation control-inspired law. Simulation and experimental results of a teleoperation scheme between a master device and an extensible continuum slave manipulator using the new controller are presented. Two novel user interface approaches to the teleoperation of continuum robots are also presented. In the first, mappings from a six Degree-of-Freedom (DoF) rigid-link robotic arm to a nine degree-of-freedom continuum robot are synthesized, analyzed, and implemented, focusing on their potential for creating an intuitive operational interface. Tests were conducted across a range of planar and spatial tasks, using fifteen participant operators. The results demonstrate the feasibility of the approach, and suggest that it can be effective independent of the prior robotics, gaming, or teleoperative experience of the operator. In the second teleoperation approach, a novel nine degree-of-freedom input device for the teleoperation of extensible continuum robots is introduced. As opposed to previous works limited by kinematically dissimilar master devices or restricted degrees-of-freedom, the device is capable of achieving configurations identical to a three section continuum robot, and simplifying the control of such manipulators. The thesis discusses the design of the control device and its construction. The implementation of the new master device is discussed and the effectiveness of the system is reported

Continuum robots and underactuated grasping

We discuss the capabilities of continuum (continuous backbone) robot structures in the performance of under-actuated grasping. Continuum robots offer the potential of robust grasps over a wide variety of object classes, due to their ability to adapt their shape to interact with the environment via non-local continuum contact conditions. Furthermore, this capability can be achieved with simple, low degree of freedom hardware. However, there are practical issues which currently limit the application of continuum robots to grasping. We discuss these issues and illustrate via an experimental continuum grasping case study. <br><br> <i>This paper was presented at the IFToMM/ASME International Workshop on Underactuated Grasping (UG2010), 19 August 2010, Montréal, Canada.</i&gt

Computational Modeling and Experimental Characterization of Pneumatically Driven Actuators for the Development of a Soft Robotic Arm

abstract: Soft Poly-Limb (SPL) is a pneumatically driven, wearable, soft continuum robotic arm designed to aid humans with medical conditions, such as cerebral palsy, paraplegia, cervical spondylotic myelopathy, perform activities of daily living. To support user's tasks, the SPL acts as an additional limb extending from the human body which can be controlled to perform safe and compliant mobile manipulation in three-dimensional space. The SPL is inspired by invertebrate limbs, such as the elephant trunk and the arms of the octopus. In this work, various geometrical and physical parameters of the SPL are identified, and behavior of the actuators that comprise it are studied by varying their parameters through novel quasi-static computational models. As a result, this study provides a set of engineering design rules to create soft actuators for continuum soft robotic arms by understanding how varying parameters affect the actuator's motion as a function of the input pressure. A prototype of the SPL is fabricated to analyze the accuracy of these computational models by performing linear expansion, bending and arbitrary pose tests. Furthermore, combinations of the parameters based on the application of the SPL are determined to affect the weight, payload capacity, and stiffness of the arm. Experimental results demonstrate the accuracy of the proposed computational models and help in understanding the behavior of soft compliant actuators. Finally, based on the set functional requirements for the assistance of impaired users, results show the effectiveness of the SPL in performing tasks for activities of daily living.Dissertation/ThesisMasters Thesis Mechanical Engineering 201

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

A New Approach to Dynamic Modeling of Continuum Robots

ABSTRACT In this thesis, a new approach for developing practically realizable dynamic models for continuum robots is proposed. Based on the new dynamic models developed, a novel technique for analyzing the capabilities of continuum manipulators to be employed in various real world applications has also been proposed and developed. A section of a continuum arm is modeled using lumped model elements (masses, springs and dampers). It is shown that this model, although an approximation to a continuum structure, can be used to conveniently analyze the dynamics of the arm with suitable tradeoff in accuracy of modeling. This relatively simple model is more plausible to implement in an actual real-time controller when compared to other techniques of modeling continuum arms. Principles of Lagrangian dynamics are used to derive the expressions for the generalized forces in the system. The force exerted by McKibben actuators at different pressure level - length pairs is characterized and is incorporated into this dynamic model. The constraints introduced in the analytical model conform to the physical and operational limitations of the Octarm VI continuum robot manipulator. The model is validated by comparing the results of numerical simulation with the physical measurements of a continuum arm prototype built using McKibben actuators. Based on the new lumped parameter dynamic model developed for continuum robots, a technique for deducing measures of manipulability, forces and impacts that can be sustained or imparted by the tip of a continuum robot has been developed. These measures are represented in the form of ellipsoids whose volume and orientation gives information about the various functional capabilities (end effector velocities, forces and impacts) of the arm at a particular configuration. The above mentioned ellipsoids are exemplified for different configurations of the continuum section arm and their physical significances are analyzed. The new techniques proposed and methodologies adopted in this thesis supported by experimental results represent a significant contribution to the field of continuum robots

Nonlinear Control Techniques for Robot Manipulators

This Masters thesis describes the design and implementation of control strategies for the following topics of research: i) Whole Arm Grasping Control for Redundant Robot Manipulators, ii) Neural Network Grasping Controller for Continuum Robots and, iii) Coordination Control for Haptic and Teleoperator Systems. An approach to whole arm grasping of objects using redundant robot manipulators is presented. A kinematic control which facilitates the encoding of both the end-effector position, as well as body self-motion positioning information as a desired trajectory signal for the manipulator joints is developed. An approach is presented to whole arm grasping control for continuum robots. The grasping controller is developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties. Lastly, two controllers are developed for nonlinear haptic and teleoperator systems for coordination of the master and slave systems

Control Techniques for Robot Manipulator Systems with Modeling Uncertainties

This dissertation describes the design and implementation of various nonlinear control strategies for robot manipulators whose dynamic or kinematic models are uncertain. Chapter 2 describes the development of an adaptive task-space tracking controller for robot manipulators with uncertainty in the kinematic and dynamic models. The controller is developed based on the unit quaternion representation so that singularities associated with the otherwise commonly used three parameter representations are avoided. Experimental results for a planar application of the Barrett whole arm manipulator (WAM) are provided to illustrate the performance of the developed adaptive controller. The controller developed in Chapter 2 requires the assumption that the manipulator models are linearly parameterizable. However there might be scenarios where the structure of the manipulator dynamic model itself is unknown due to difficulty in modeling. One such example is the continuum or hyper-redundant robot manipulator. These manipulators do not have rigid joints, hence, they are difficult to model and this leads to significant challenges in developing high-performance control algorithms. In Chapter 3, a joint level controller for continuum robots is described which utilizes a neural network feedforward component to compensate for dynamic uncertainties. Experimental results are provided to illustrate that the addition of the neural network feedforward component to the controller provides improved tracking performance. While Chapter\u27s 2 and 3 described two different joint controllers for robot manipulators, in Chapter 4 a controller is developed for the specific task of whole arm grasping using a kinematically redundant robot manipulator. The whole arm grasping control problem is broken down into two steps; first, a kinematic level path planner is designed which facilitates the encoding of both the end-effector position as well as the manipulators self-motion positioning information as a desired trajectory for the manipulator joints. Then, the controller described in Chapter 3, which provides asymptotic tracking of the encoded desired joint trajectory in the presence of dynamic uncertainties is utilized. Experimental results using the Barrett Whole Arm Manipulator are presented to demonstrate the validity of the approach

Design and analysis of a wire-driven flexible manipulator for bronchoscopic interventions

Bronchoscopic interventions are widely performed for the diagnosis and treatment of lung diseases. However, for most endobronchial devices, the lack of a bendable tip restricts their access ability to get into distal bronchi with complex bifurcations. This paper presents the design of a new wire-driven continuum manipulator to help guide these devices. The proposed manipulator is built by assembling miniaturized blocks that are featured with interlocking circular joints. It has the capability of maintaining its integrity when the lengths of actuation wires change due to the shaft flex. It allows the existence of a relatively large central cavity to pass through other instruments and enables two rotational degrees of freedom. All these features make it suitable for procedures where tubular anatomies are involved and the flexible shafts have to be considerably bent in usage, just like bronchoscopic interventions. A kinematic model is built to estimate the relationship between the translations of actuation wires and the manipulator tip position. A scale-up model is produced for evaluation experiments and the results validate the performance of the proposed mechanism

Modeling, Control, and Motion Analysis of a Class of Extensible Continuum Manipulators

In this dissertation, the development of a kinematic model, a configuration-space controller, a master-slave teleoperation controller, along with the analysis of the self-motion properties for redundant, extensible, continuous backbone (continuum) ``trunk and tentacle\u27 manipulators are detailed. Unlike conventional rigid-link robots, continuum manipulators are robots that can bend at any point along their backbone, resulting in new and unique modeling and control issues. Taken together, these chapters represent one of the first efforts towards devising model-based controllers of such robots, as well as characterizing their self-motion in its simplest form. Chapter 2 describes the development of a convenient set of generalized, spatial forward kinematics for extensible continuum manipulators based on the robot\u27s measurable variables. This development, takes advantage of the standard constant curvature assumption made for such manipulators and is simpler and more intuitive than the existing kinematic derivations which utilize a pseudo-rigid link manipulator. In Chapter 3, a new control strategy for continuum robots is presented. Control of this emerging new class of robots has proved difficult due to the inherent complexity of their dynamics. Using a recently established full Lagrangian dynamic model, a new nonlinear model-based control strategy (sliding-mode control) for continuum robots is introduced. Simulation results are illustrated using the dynamic model of a three-section, six Degree-of-Freedom, planar continuum robot and an experiment was conducted on the OctArm 9 Degree-of-Freedom continuum manipulator. In both the simulation and experiment, the results of the sliding-mode controller were found to be significantly better than a standard inverse-dynamics PD controller. In Chapter 4, the nature of continuum manipulator self-motion is studied. While use of the redundant continuum manipulator self-motion property (configuration changes which leave the end-effector location fixed) has been proposed, the nature of their null-spaces has not previously been explored. The manipulator related resolved-motion rate inverse kinematics which are based on the forward kinematics described in Chapter 2, are used. Based on these derivations, the self-motion of a 2-section, extensible redundant continuum manipulator in planar and spatial situations (generalizable to n-sections) is analyzed. The existence of a single self-motion manifold underlying the structures is proven, and simple self-motion cases spanning the null-space are introduced. The results of this analysis allow for a better understanding of general continuum robot self-motions and relate their underlying structure to real world examples and applications. The results are supported by experimental validation of the self-motion properties on the 9 Degree-of-Freedom OctArm continuum manipulator. In Chapter 5, teleoperation control of a kinematically redundant, continuum slave robot by a non-redundant, rigid-link master system is described. This problem is novel because the self-motion of the redundant robot can be utilized to achieve secondary control objectives while allowing the user to only control the tip of the slave system. To that end, feedback linearizing controllers are proposed for both the master and slave systems, whose effectiveness is demonstrated using numerical simulations and experimental results (using the 9 Degree-of-Freedom OctArm continuum manipulator as the slave system) for trajectory tracking as well as singularity avoidance subtask

Operational Strategies for Continuum Manipulators

We introduce a novel, intuitive user interface for continuum manipulators through the use of various joystick mappings. This user interface allows for the effective use of continuum manipulators in the lab and in the field. A novel geometric approach is developed to produce a more intuitive understanding of continuum manipulator kinematics. Using this geometric approach we derive the first closed-form solution to the inverse kinematics problem for continuum robots. Using the derived inverse kinematics to convert from workspace coordinates to configuration space coordinates we develop a potential-field path planner for continuum manipulators