Optimization of polynomial trajectories for robotic manipulators

In this thesis, a method is presented to construct minimum-time robot trajectories for predefined Cartesian end-effector path in a workspace containing obstacles. The method is preferably applied to a geometric collision-free path of a SCARA robot by using the theories of Bezier, B-spline, and parabolic blending curves. The motion of the manipulator is defined by Cartesian control points and represented by a sequence of generated Cartesian knots along the end-effector path which is transformed into sets of joint displacements with one set for each joint. Cubic spline functions are then used to fit the sequence of joint displacements for each joint. The minimum-time trajectory planning problem is formulated as the problem of minimizing the total traveling time subject to constraints on joint positions, velocities, accelerations, jerks, torques and end-effector acceleration. The modified pattern search goal programming method is proposed to solve this nonlinear optimization problem. The computer program, ROBOPATH, has been written to implement the algorithm for a manipulator with two links and two degrees of freedom. The examples show the algorithm to be a useful tool in the design of manipulators, robot tasks and workcells. The results show that different locations of a path and different path shapes resulted in different total traveling times. Also, as a result, approximation curve techniques gave shorter total traveling time than the interpolation curve technique

Simulators, graphic

Includes bibliographical references (pages 1607-1608).There are many situations in which a computer simulation with a graphic display can be very useful in the design of a robotic system. First of all, when a robot is planned for an industrial application, there are many commercially available arms that can be selected. A graphics-based simulation would allow the manufacturing engineer to evaluate alternative choices quickly and easily. The engineer can also use such a simulation tool to design interactively the workcell in which the robot operates and integrate the robot with other systems, such as part feeders and conveyors with which it must closely work. Even before the workcell is assembled or the arm first arrives, the engineer can optimize the placement of the robot with respect to the fixtures it must reach and ensure that the arm is not blocked by supports. By being able to evaluate workcell designs off-line and away from the factory floor, changes can be made without hindering factory production and thus the net productivity of the design effort can be increased

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

A Task-based Design Methodology for Robotic Exoskeletons

This study is aimed at developing a task-based methodology for the design of robotic exoskeletons. This is in contrast to prevailing research efforts, which attempt to mimic the human limb, where each human joint is given an exoskeleton counter-joint. Rather, we present an alternative systematic design approach for the design of exoskeletons that can follow the complex three-dimensional motions of the human body independent of anatomical measures and landmarks. With this approach, it is not necessary to know the geometry of the targeted limb but rather to have a description of its motion at the point of attachment.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version

Proceedings of the NASA Conference on Space Telerobotics, volume 3

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas