Automated design of modular field robots

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1995.Includes bibliographical references (leaves 80-84).by Nathaniel Rutman.M.S

Robust Spline Path Following for Redundant Mechanical Systems

Path following controllers make the output of a control system approach and traverse a pre-specified path with no a priori time-parametrization. The first part of the thesis implements a path following controller for a simple class of paths, based on transverse feedback linearization (TFL), which guarantees invariance of the path to be followed. The coordinate and feedback transformation employed allows one to easily design control laws to generate arbitrary desired motions on the path for the closed-loop system. The approach is applied to an uncertain and simplified model of a fully actuated robot manipulator for which none of the dynamic parameters are measured. The controller is made robust to modelling uncertainties using Lyapunov redesign. The experimental results show a substantial improvement when using the robust controller for path following versus standard state feedback. In the second part of the thesis, the class of paths and systems considered are extended. We present a method for path following control design applicable to framed curves generated by spline interpolating waypoints in the workspace of kinematically redundant mechanical systems. The class of admissible paths include self-intersecting curves. Kinematic redundancies of the system are resolved by designing controllers that solve a suitably defined constrained quadratic optimization problem that can be easily tuned by the designer to achieve various desired poses. The class of redundant systems considered include mobile manipulators for a large class of wheeled ground vehicles. The result is a path following controller that simultaneously controls the manipulator and mobile base, without any trajectory planning performed on the mobile base. The approach is experimentally verified using the robust controller developed in the first part of the thesis on a 4-degree-of-freedom (4DOF) redundant manipulator and a mobile manipulator system with a differential drive base

Compensating for model uncertainty in the control of cooperative field robots

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2002.Includes bibliographical references (p. 113-123).Current control and planning algorithms are largely unsuitable for mobile robots in unstructured field environment due to uncertainties in the environment, task, robot models and sensors. A key problem is that it is often difficult to directly measure key information required for the control of interacting cooperative mobile robots. The objective of this research is to develop algorithms that can compensate for these uncertainties and limitations. The proposed approach is to develop physics-based information gathering models that fuse available sensor data with predictive models that can be used in lieu of missing sensory information. First, the dynamic parameters of the physical models of mobile field robots may not be well known. A new information-based performance metric for on-line dynamic parameter identification of a multi-body system is presented. The metric is used in an algorithm to optimally regulate the external excitation required by the dynamic system identification process. Next, an algorithm based on iterative sensor planning and sensor redundancy is presented to enable field robots to efficiently build 3D models of their environment. The algorithm uses the measured scene information to find new camera poses based on information content. Next, an algorithm is presented to enable field robots to efficiently position their cameras with respect to the task/target. The algorithm uses the environment model, the task/target model, the measured scene information and camera models to find optimum camera poses for vision guided tasks. Finally, the above algorithms are combined to compensate for uncertainties in the environment, task, robot models and sensors. This is applied to a cooperative robot assembly task in an unstructured environment.(cont.) Simulations and experimental results are presented that demonstrate the effectiveness of the above algorithms on a cooperative robot test-bed.by Vivek Anand Sujan.Ph.D

A graph-theory-based C-space path planner for mobile robotic manipulators in close-proximity environments

In this thesis a novel guidance method for a 3-degree-of-freedom robotic manipulator arm in 3 dimensions for Improvised Explosive Device (IED) disposal has been developed. The work carried out in this thesis combines existing methods to develop a technique that delivers advantages taken from several other guidance techniques. These features are necessary for the IED disposal application. The work carried out in this thesis includes kinematic and dynamic modelling of robotic manipulators, T-space to C-space conversion, and path generation using Graph Theory to produce a guidance technique which can plan a safe path through a complex unknown environment. The method improves upon advantages given by other techniques in that it produces a suitable path in 3-dimensions in close-proximity environments in real time with no a priori knowledge of the environment, a necessary precursor to the application of this technique to IED disposal missions. To solve the problem of path planning, the thesis derives the kinematics and dynamics of a robotic arm in order to convert the Euclidean coordinates of measured environment data into C-space. Each dimension in C-space is one control input of the arm. The Euclidean start and end locations of the manipulator end effector are translated into C-space. A three-dimensional path is generated between them using Dijkstra’s Algorithm. The technique allows for a single path to be generated to guide the entire arm through the environment, rather than multiple paths to guide each component through the environment. The robotic arm parameters are modelled as a quasi-linear parameter varying system. As such it requires gain scheduling control, thus allowing compensation of the non-linearities in the system. A Genetic Algorithm is applied to tune a set of PID controllers for the dynamic model of the manipulator arm so that the generated path can then be followed using a conventional path-following algorithm. The technique proposed in this thesis is validated using numerical simulations in order to determine its advantages and limitations