Doctor of Philosophy

Soft automation employs multi-functional robotic manipulators where dexterity, versatility and reconfigurability are now becoming key issues. For manipulators used in these circumstances, hyper-redundancy in configuration is essential. A typical application envisaged, is manipulator movement in unpredictable surroundings such as navigation amongst branches and foliage in automated fruit picking. This requires motion of a manipulator in an unmapped dynamic environment to find its way to the goal i.e. the fruit. To date, centralized control architectures have proven impractical for the control of redundant systems because the full environment needs to be mapped, there are time constraints on the computation required and, simultaneously, algorithms for obstacle avoidance must be enacted. Decentralized control of manipulators complements modular construction because the need for a full environment reconstruction in one master controller is bypassed by having localized sub-goals for each module. Time constraints are removed because the control algorithms are much simpler. Obstacle avoidance is localized. Manipulators constructed modularly are effective because they allow for reconfiguration and ease of fault diagnosis. For modular manipulators to be a more effective option as a subclass of robots, the conditions under which the interactive movements of modules are stable become a major issue. When a general review of hyper-redundant manipulators was undertaken, no published implementation of Modular Decentralized Control (MDC) was discovered. This thesis explored the use of a modular decentralized technique to create stable control of a redundant manipulator system. The computational burden was minimized by restricting inverse kinematics to within each module. Advantages of the approach taken were the ease of implementation of obstacle avoidance, reconfigurability and fault tolerance. Having firstly simulated a MATLAB version of stable motion using MDC on a modular manipulator with up to six identical modules, the technique was extended with state space analysis to redefine the limits of stable control of a hyper-redundant manipulator. The MDC study mapped motion profile types that were dependant on the initial manipulator configuration and goal position and, thereby, investigated possible instabilities in the system. A two-link, single degree of freedom system was initially explicated followed by an extension of the stability analysis to an n-module two degree of freedom system. A stability theory utilizing decentralized control was formed. Simulation results showed dynamic motion, path generation and obstacle avoidance capabilities in unmapped environments to be stable. The modeling redefined the bounds of stable control, showing that classical stability via Root Locus, now required only two roots from the characteristic equation to be stable for a selection of path trajectory to the goal to be found. The remaining roots could be unstable in traversing to the goal and settling at a marginal stability point when the goal was reached. The marginal stability was a reflection of the pseudo-independence given to each module in seeking the goal and differed radically from a standard Root Locus analysis and interpretation of stability. A hyper-redundant Reconfigurable Modular Manipulator System (RMMS) was designed and built to implement the MDC technique in a real world environment. From an initial design, five modules were constructed and control algorithms embedded appropriate to their position in a five-segment robotic manipulator. A stereoscopic vision system was attached to the end of the manipulator which supplied real time data on a goal in 3D Cartesian space. The data was supplied to the first module of the arm and subsequently to all others by localized homogenous transformation. The manipulator was tested for goal seeking, path following, obstacle avoidance, fault tolerance and reconfigurability. The arm produced stable motion and satisfied the criteria as hypothesized in the theory.

Thesis (M.S.)--Ohio University, June, 2001. / Title from PDF t.p.

Thesis (M.S.)--Ohio University, March, 1999. / Title from PDF t.p.

Thesis (M.S.)--Ohio University, November, 2002. / Title from PDF t.p. Includes bibliographical references (leaves 77-79).

Thesis (M.S.)--Ohio University, June, 1997. / Title from PDF t.p.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 112-121). Also available in electronic version.

As robotic manipulators become more prevalent, particularly in hazardous environments or for repetitive tasks, demand continues for increased performance and decreased cost. In some applications, both can be achieved by reducing the weight of the manipulator. However, reduced weight often leads to significant structural flexibility and vibration which, for most tasks, is generally regarded as detrimental to performance. Although there has been a great deal of research in the area of controlling flexible manipulators to follow a desired trajectory, much less work has been directed towards choosing the trajectory itself. The objective of this work is to optimize point-to-point motions in joint space to reduce vibration. This problem is formulated as one of functional optimization and the applicable methods of solution are reviewed. An indirect method is chosen that allows modular software development by preserving the integrity of existing nonlinear dynamics models. Numerical results are compared with trajectories generated by other means and show a significant reduction in vibration possible by optimization, particularly for varying joint paths. Finally, the effectiveness of the trajectory optimization scheme is further evaluated for high-speed, large-angle motions of an experimental nonplanar two-link flexible manipulator. Such results are lacking in the literature, but are very important for assessing the utility of trajectory optimization in the presence of modelling and tracking errors. Again, significant reductions in vibration are demonstrated by using the global optimization approach for trajectory generation. / Graduate

M.Ing. (Mechanical Engineering) / In this study a manipulator was developed by using system design methods. The main aim was to develop a robot which could be used as a packer in an industrial environment. Pneumatic silinders have been used with great success but up to now seldom in areas where positional accuracy is required. To design a manipulator which is able to operate in a varying work space it must be supplied with specialized sensors. For this reason research was done into image processing. Most of the relevant techniques of image processing arc discussed shortly with particular emphasis on the method of moment invariants for object recognition. Another important aspect covered in the project is the way by which articulated mechanical systems can be modelled kinematically and dynamically. The kinematical description was especially studied and in particular the method introduced by Denavit and Hartenberg and the method of general matrix transformations.

This thesis discusses the possibility of attaining closed loop end piece control of a servo controlled manipulator by externally modifying the independent control loop set point of each robot link. This procedure leaves the existing servo control loops intact and thus has the benefit of acquiring the advantages of an advanced control strategy while retaining the inherent reliability and stability of the existing control loops. Algorithms are proposed for compensating for known disturbance torques, eliminating end piece position errors, and applying specified forces to the surroundings with the end piece. These algorithms are demonstrated for the three degree of freedom case using a simulation package ROBSIM.FOR which simulates the response of a servo controlled manipulator to set point inputs. To compensate for known disturbance torques the torques generated by the robot control system are assumed to be directly proportional to the changes in set points. These approximate relations are used to estimate the adjustment in set points necessary to generate the required additional joint torques. Simulation results show that this method is effective in compensating for gravity disturbance torques. The Jacobian relates changes in position of the end piece to changes in joint angles. Using the Jacobian combined with a weighting factor to prevent overshoot an algorithm is developed which drives end piece position errors to zero. The transpose of the Jacobian is used to relate forces exerted on the surroundings by the end piece to generated joint torques. The required torques are created by adjusting the set points. Simulation results indicate that this method can be used to exert specified forces. Force control is more difficult to achieve than position control because the robot interacts physically with its surroundings. The ability of the robot to exert forces depends strongly on the robot's configuration. All work in this thesis can be generated using the single program ROBSIM.FOR. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate