A modal approach to hyper-redundant manipulator kinematics

This paper presents novel and efficient kinematic modeling techniques for “hyper-redundant” robots. This approach is based on a “backbone curve” that captures the robot's macroscopic geometric features. The inverse kinematic, or “hyper-redundancy resolution,” problem reduces to determining the time varying backbone curve behavior. To efficiently solve the inverse kinematics problem, the authors introduce a “modal” approach, in which a set of intrinsic backbone curve shape functions are restricted to a modal form. The singularities of the modal approach, modal non-degeneracy conditions, and modal switching are considered. For discretely segmented morphologies, the authors introduce “fitting” algorithms that determine the actuator displacements that cause the discrete manipulator to adhere to the backbone curve. These techniques are demonstrated with planar and spatial mechanism examples. They have also been implemented on a 30 degree-of-freedom robot prototype

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

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

Head-raising of snake robots based on a predefined spiral curve method

© 2018 by the authors. A snake robot has to raise its head to acquire a wide visual space for planning complex tasks such as inspecting unknown environments, tracking a flying object and acting as a manipulator with its raising part. However, only a few researchers currently focus on analyzing the head-raising motion of snake robots. Thus, a predefined spiral curve method is proposed for the head-raising motion of such robots. First, the expression of the predefined spiral curve is designed. Second, with the curve and a line segments model of a snake robot, a shape-fitting algorithm is developed for constraining the robot's macro shape. Third, the coordinate system of the line segments model of the robot is established. Then, phase-shifting and angle-solving algorithms are developed to obtain the angle sequences of roll, pitch, and yaw during the head-raising motion. Finally, the head-raising motion is simulated using the angle sequences to validate the feasibility of this method

Design of a Novel Long-Reach Cable-Driven Hyper-Redundant Snake-like Manipulator for Inspection and Maintenance

Robotic inspection and maintenance are gaining importance due to the number of different scenarios in which robots can operate. The use of robotic systems to accomplish such tasks has deep implications in terms of safety for human workers and can significantly extend the life of infrastructures and industrial facilities. In this context, long-reach cable-driven hyper-redundant robots can be employed to inspect areas that are difficult to reach and hazardous environments such as tanks and vessels. This paper presents a novel long-reach cable-driven hyper-redundant robot called SLIM (Snake-Like manipulator for Inspection and Maintenance). SLIM consists of a robotic arm, a pan and tilt mechanism as end-effector, and an actuation box that can rotate and around which the arm can wrap. The robot has a total of 15 degrees of freedom and, therefore, for the task of positioning the tool centre point in a bi-dimensional Cartesian space with a specific attitude, it has 10 degrees of redundancy. The robot is designed to operate in harsh environments and high temperatures and can deploy itself up to about 4.8 m. This paper presents the requirements that drove the design of the robot, the main aspects of the mechanical and electronic systems, the control strategy, and the results of preliminary experimental tests performed with a physical prototype to evaluate the robot performances

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

An optimization approach for the inverse kinematics of a highly redundant robot

This paper describes a robot with 12 degrees of freedom for pick-and-place operations using bricks. In addition, an optimization approach is proposed, which determines the state of each joint (that establishes the pose for the robot) based on the target position while minimizing the effort of the servomotors avoiding the inverse kinematics problem, which is a hard task for a 12 DOF robot manipulator. Therefore, it is a multi-objective optimization problem that will be solved using two optimization methods: the Stretched Simulated Annealing method and the NSGA II method. The experiments conducted in a simulation environment prove that the proposed approach is able to determine a solution for the inverse kinematics problem. A real robot formed by several servomotors and a gripper is also presented in this research for validating the solutions.info:eu-repo/semantics/publishedVersio

Design of Massive Actuators For 3D Robot Manipulators

In this paper, a novel parallel manipulator with discrete control system is developed. An efficient method such as Inverse Static Analysis (ISA) is employed to determine the state of each actuator on parallel manipulator when the position or force of manipulator is already known. The designing a parallel manipulator with 16 actuators which are controlled discretely is a must because the mechanism will use artificial methods in dealing with the ISA problem. In this approach, mathematical model is not required. The research method used simulation software and hardware testing with the case of parallel manipulator with 16 actuators. Simulations with typical desired force inputs are presented and a good performance of the mechanism is obtained. The results showed that the parallel manipulator has the Root Mean Squared Error (RMSE) has less than 3% and can be used for artificial intelligence implementation

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored