Inverse Kinematics of a Hyper-Redundant Robotic Manipulator

Serial robots, Snake or, Worm robots, Tentacle robots or continuum robots are known as hyperredundant robots and possess very large degrees of kinematics redundancy. Inverse kinematics of hyper-redundant robots can have infinite number of solutions, which is a great challenge against position control of such robots. Various techniques have so far been proposed for inverse kinematics of hyper-redundant robots that involve wide range of mathematics, which include nonlinear optimization, Artificial Neural Network, Fuzzy System etc. In this paper a new technique has been proposed that assumes a configuration with a virtual layer, where probable singularities are included. In the successive steps the singularities are removed following some geometric propositions to have the final version of the configuration, which ultimately gives the inverse kinematics of the hyperredundant robot. Mathematics involved in this new technique is the traditional inverse kinematics solution of two link subrobots, which are selected to satisfy the geometric propositions. The proposed technique has been tested on four link and six link robots and some comparison are made with one of the recent techniques known as ANFIS

Position control of a four link hyper redundant robotic manipulator

Hyper-Redundant robotic manipulators like Serial robots, Snake robots, Tentacle robots or Continuum robots have very large number of degrees of kinematics redundancy. Position control of such a robotic manipulator comprising of more than three links and articulated joints is a big challenge due to the involvement of large number of trigonometric terms in its inverse kinematics equations. In this paper, a simple algorithm for the inverse kinematics solution (IKS) of a four-link serial robotic manipulator has been proposed, which is then validated experimentally. The proposed method divides the robot into two two-link virtual sub-robot and solves the inverse kinematics analytically for joint variables of each sub-robot successively. A validation experiment was conducted on a 4-link prototype to check the validity of the proposed algorithm. The experimental results showed satisfactory results with good repeatability

Experimental Characterization of a Binary Actuated Parallel Manipulator

This paper describes the BAPAMAN (Binary Actuated Parallel MANipulator) series of parallel manipulators that has been conceived at LARM. Basic common characteristics of BAPAMAN series are described. In particular, it is outlined the use of a reduced number of active degrees of freedom, the use of design solutions with flexural joints and Shape Memory Alloy (SMA) actuators for achieving miniaturization, cost reduction and easy operation features. Given the peculiarities of BAPAMAN architecture, specific experimental tests have been proposed and carried out with the aim to validate the proposed design and to evaluate the practical operation performance and the characteristics of a built prototype, in particular, in terms of operation and workspace characteristics

Design and Modeling of 9 Degrees of Freedom Redundant Robotic Manipulator

In disaster areas, robot manipulators are used to rescue and clearance of sites. Because of the damaged area, they encounter disturbances like obstacles, and limited workspace to explore the area and to achieve the location of the victims. Increasing the degrees of freedom is required to boost the adaptability of manipulators to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. These robot manipulators offer a reliable way to handle the barrier challenges since they can search in places that humans can't reach. In this research paper, the 9-DOF robotic manipulator is designed, and an analytical model is developed to examine the system’s behavior in different scenarios. The kinematic and dynamic representation of the proposed model is analyzed to obtain the translation or rotation, and joint torques to achieve the expected position, velocity, and acceleration respectively. The number of degrees may be raised to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. The simulation of developed models is performed to ensure the adaptable movement of the manipulators working in distinct configurations and controlling their motion thoroughly and effectively. In the proposed configuration the joints can easily be moved to achieve the desired position of the end-effector and the results are satisfactory. The simulation results show that the redundant manipulator achieves the victim location with various configurations of the manipulator. Results reveal the effectiveness and efficacy of the proposed system

Design, Control and Motion Planning for a Novel Modular Extendable Robotic Manipulator

This dissertation discusses an implementation of a design, control and motion planning for a novel extendable modular redundant robotic manipulator in space constraints, which robots may encounter for completing required tasks in small and constrained environment. The design intent is to facilitate the movement of the proposed robotic manipulator in constrained environments, such as rubble piles. The proposed robotic manipulator with multi Degree of Freedom (m-DOF) links is capable of elongating by 25% of its nominal length. In this context, a design optimization problem with multiple objectives is also considered. In order to identify the benefits of the proposed design strategy, the reachable workspace of the proposed manipulator is compared with that of the Jet Propulsion Laboratory (JPL) serpentine robot. The simulation results show that the proposed manipulator has a relatively efficient reachable workspace, needed in constrained environments. The singularity and manipulability of the designed manipulator are investigated. In this study, we investigate the number of links that produces the optimal design architecture of the proposed robotic manipulator. The total number of links decided by a design optimization can be useful distinction in practice. Also, we have considered a novel robust bio-inspired Sliding Mode Control (SMC) to achieve favorable tracking performance for a class of robotic manipulators with uncertainties. To eliminate the chattering problem of the conventional sliding mode control, we apply the Brain Emotional Learning Based Intelligent Control (BELBIC) to adaptively adjust the control input law in sliding mode control. The on-line computed parameters achieve favorable system robustness in process of parameter uncertainties and external disturbances. The simulation results demonstrate that our control strategy is effective in tracking high speed trajectories with less chattering, as compared to the conventional sliding mode control. The learning process of BLS is shown to enhance the performance of a new robust controller. Lastly, we consider the potential field methodology to generate a desired trajectory in small and constrained environments. Also, Obstacle Collision Avoidance (OCA) is applied to obtain an inverse kinematic solution of a redundant robotic manipulator

Kinematic analysis of electroactive polymer actuators as soft and smart structures with more DoF than inputs

Electroactive polymer (EAP) actuators have been attracting the attention of researchers due to their muscle-like behaviour and unusual properties. Several modelling methods have been proposed to understand their mechanical, chemical, electrical behaviours or ‘electro-chemo-mechanical’ behaviour. However, estimating the whole shape or configuration of the EAP actuators has always been challenging due to their highly non-linear bending behaviour. This paper reports on an effective method to estimate the whole shape deflection of the EAP actuators by employing a so-called backbone approach. Tri-layer configured polypyrrole (PPy) based EAP actuators were used as a soft and smart structure with more degrees of freedom than its input. After deriving the inverse kinematic model of the actuator, its complete shape is estimated by solving the inverse kinematic model with an angle optimization (AngleOPT) method. The experimental results and numerical results have demonstrated the effectiveness of the method in estimating the highly non-linear bending behaviour of the PPy actuators and applicability of this modelling approach to other EAP actuators

Design, Control and Motion Planning for a Novel Modular Extendable Robotic Manipulator

This dissertation discusses an implementation of a design, control and motion planning for a novel extendable modular redundant robotic manipulator in space constraints, which robots may encounter for completing required tasks in small and constrained environment. The design intent is to facilitate the movement of the proposed robotic manipulator in constrained environments, such as rubble piles. The proposed robotic manipulator with multi Degree of Freedom (m-DOF) links is capable of elongating by 25% of its nominal length. In this context, a design optimization problem with multiple objectives is also considered. In order to identify the benefits of the proposed design strategy, the reachable workspace of the proposed manipulator is compared with that of the Jet Propulsion Laboratory (JPL) serpentine robot. The simulation results show that the proposed manipulator has a relatively efficient reachable workspace, needed in constrained environments. The singularity and manipulability of the designed manipulator are investigated. In this study, we investigate the number of links that produces the optimal design architecture of the proposed robotic manipulator. The total number of links decided by a design optimization can be useful distinction in practice. Also, we have considered a novel robust bio-inspired Sliding Mode Control (SMC) to achieve favorable tracking performance for a class of robotic manipulators with uncertainties. To eliminate the chattering problem of the conventional sliding mode control, we apply the Brain Emotional Learning Based Intelligent Control (BELBIC) to adaptively adjust the control input law in sliding mode control. The on-line computed parameters achieve favorable system robustness in process of parameter uncertainties and external disturbances. The simulation results demonstrate that our control strategy is effective in tracking high speed trajectories with less chattering, as compared to the conventional sliding mode control. The learning process of BLS is shown to enhance the performance of a new robust controller. Lastly, we consider the potential field methodology to generate a desired trajectory in small and constrained environments. Also, Obstacle Collision Avoidance (OCA) is applied to obtain an inverse kinematic solution of a redundant robotic manipulator