SYNOPSIS: HYPER REDUNDANT MANIPULATORS
Objective:
The central idea of this project is to develop a redundant manipulator to work around obstacles and to reach inaccessible locations. Avoidance in its way towards the plants which are inhospitable to human being due to number of reasons like, high temperature, presence of toxic or radioactive substances demand such manipulators. Redundancy is required for obstacle avoidance (a manipulator is said to have redundant links if it has degrees of freedom more than required to reach a point. The present project is intended to meet demands of a complicated environment by harnessing the potential of redundant manipulator to move in a serpentine fashion.
View:
The term hyper redundant is refers to redundant manipulators with very large degrees of freedom. These manipulators are analogous in morphology to snakes, elephant trunk and tentacles. For manipulators to be an effective option in soft automation, they require redundancy and veracity. Methods of differential geometry are used to formulate equations which guarantee that sections of the manipulator are confined to the tunnels, and therefore avoid obstacles. A hyper redundant manipulator is a redundant manipulator in which the number of redundant degrees of freedom is large or infinite. These manipulators are naturally suited to operation in highly constrained environments. Proposed tasks for future robotic systems, ranging from space exploration to medical devices will require robotic device and components that are simple,
robust, lightweight, inexpensive, and easy to control. Hyper redundant binary systems have been proposed to meet this need. It has been shown that performance of a binary robotic system approaches that of a continuous system, as the no of DOF increases. However, high DOF systems are not feasible with conventional components. A major limitation is the actuator technology. In recent years important progress has been made in the area of dielectric polymer actuators.
A “backbone curve” of constant length can be defined which exactly captures the continuous manipulator shape. In the case of many discrete links, the essential macroscopic features of the manipulator can be captured by a continuous backbone curve of the same length as the sum of manipulator can be captured by a continuous backbone curve of the same length as the sum of the link lengths. The obstacle avoidance computation can be performed using the continuous backbone curve, which is then used via a “fitting” procedure, to define the joint angles of a discrete-linked manipulator.
fig. Joints of a manipulator
For increased redundancy, the modeling and design procedures become more complex. This results in more complex algorithms which increase computational delays, again complicating the systems controllability. To control redundant reconfigurable systems, it has been found that decentralized control architectures are desirable. Current research in multi-robot system has produced frameworks for team motion co-ordination as well as novel communication methods for self reconfigurable robots.
Steps Involved:
Path Planning and Obstacle Avoidance:
Intermediate path points for the end effectors are required for moving from start to goal point; also the manipulator should avoid obstacles. Initially we tried to test the traditional "Potential Field approach" graphically in OpenGL. It is very difficult to find a potential function applicable to all obstacles. We oncluded that potential field approach is not at all practical, as the manipulator tends to vibrate near the obstacles.
Next we have explored through another approach called: "Visibility Graph Search". This along with Inverse Kinematics has proved to be quite feasible. Though Inverse Kinematics for redundant manipulators is not easy to handle, one can simplify the InverseKinematics for 4 DOF parallel plane, serial manipulators. Finally, we will also demonstrate Path Planning and Obstacle Avoidance using Genetic Algorithm .
Manipulator/Work cell Design and Development:
In our three-link manipulator, links would be made of a light and sturdy composite material called "Perspex". The links would be driven by stepper motors. The following figure in the next page gives the overall look of our proposed design. Roller supports to links are given to avoid sagging. The design is portable and can be easily moved from one place to another.
Deriving articulate arm kinematic model (using forward kinematics):
A 3-DOF articulated arm is considered as the next example for obtaining the transformation matrix for the endpoint using forward kinematics technique.
An articulated arm is a 3-DOF manipulator with three revolute joints, that is an RRR arm configuration as shown in fig . The axes of joint 2 and joint 3 are parallel and axis of joint 1 is perpendicular to these two. At the end of the arm, a faceplate is provided to attach the wrist.
To determine the “ arm point” transformation matrix , the frames are assigned first as shown in fig. The resulting joint –link parameters are tabulated in table. For all the three joints, joint –offsets are assumed to be zero.
Fig. Joint-link parameters for articulated arm
Fig. Frame assignment for articulated arm
=perpendicular distance between two arms
The link transformation matrices are


Control:
Keeping the obstacles under consideration, redundancy resolution schemes will be developed to maximize the dexterous performance of the manipulator. We need to find the time behavior of the force and torques to
be delivered by the joint actuators so as to ensure the execution of the desired trajectories. Control of end-effectors motion demands an accurate analysis of the characteristic of the mechanical structure, actuators etc. Therefore manipulator control is ensured to the closure of feedback loops, by
computing the deviation between the reference inputs and the data provided by the proprioceptive sensors. A feedback control system is capable to satisfy accuracy requirements on the execution of the prescribed
trajectories. Servo and model-based control strategies will be developed and experimentally evaluated with respect to their performance and cost in order to finalize the most suitable control scheme. In fact much of the challenge of the design and its efficient use focuses on this aspect. The data generated by the path-planning program is fed to control software called LABVIEW. This software converts the digital signal to analog using a control card called FLEX MOTION PC1-6c. The specifications of this control card are shown after few pages. The signal is fed to motor, which drives the manipulator using the gear head. The encoder senses the position of the joints at regular interval oftime. This provides data for feedback control in terms of velocity and position. It is converted to analog signal using the same control card. Thus the feedback loop is completed and the desired motion is obtained.



















