An inverse kinematics algorithm for a highly redundant variable-geometry-truss manipulator

A new class of robotic arm consists of a periodic sequence of truss substructures, each of which has several variable-length members. Such variable-geometry-truss manipulator (VGTMs) are inherently highly redundant and promise a significant increase in dexterity over conventional anthropomorphic manipulators. This dexterity may be exploited for both obstacle avoidance and controlled deployment in complex workspaces. The inverse kinematics problem for such unorthodox manipulators, however, becomes complex because of the large number of degrees of freedom, and conventional solutions to the inverse kinematics problem become inefficient because of the high degree of redundancy. A solution is presented to this problem based on a spline-like reference curve for the manipulator's shape. Such an approach has a number of advantages: (1) direct, intuitive manipulation of shape; (2) reduced calculation time; and (3) direct control over the effective degree of redundancy of the manipulator. Furthermore, although the algorithm was developed primarily for variable-geometry-truss manipulators, it is general enough for application to a number of manipulator designs

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

Follow-the-Leader Control for the PIPS Prototype Hardware

This report describes the payload inspection and processing system (PIPS), an automated system programmed off-line for inspection of space shuttle payloads after integration and prior to launch. PIPS features a hyper-redundant 18-degree of freedom (DOF) serpentine truss manipulator capable of snake like motions to avoid obstacles. During the summer of 1995, the author worked on the same project, developing a follow-the-leader (FTL) algorithm in graphical simulation which ensures whole arm collision avoidance by forcing ensuing links to follow the same tip trajectory. The summer 1996 work was to control the prototype PIPS hardware in follow-the-leader mode. The project was successful in providing FTL control in hardware. The STS-82 payload mockup was used in the laboratory to demonstrate serpentine motions to avoid obstacles in a realistic environment

Automated path planning of the Payload Inspection and Processing System

The Payload Changeout Room Inspection and Processing System (PIPS) is a highly redundant manipulator intended for performing tasks in the crowded and sensitive environment of the Space Shuttle Orbiter payload bay. Its dexterity will be exploited to maneuver the end effector in a workspace populated with obstacles. A method is described by which the end effector of a highly redundant manipulator is directed toward a target via a Lyapunov stability function. A cost function is constructed which represents the distance from the manipulator links to obstacles. Obstacles are avoided by causing the vector of joint parameters to move orthogonally to the gradient of the workspace cost function. A C language program implements the algorithm to generate a joint history. The resulting motion is graphically displayed using the Interactive Graphical Robot Instruction Program (IGRIP) produced by Deneb Robotics. The graphical simulation has the potential to be a useful tool in path planning for the PIPS in the Shuttle Payload Bay environment

A Fibonacci control system with application to hyper-redundant manipulators

We study a robot snake model based on a discrete linear control system involving Fibonacci sequence and closely related to the theory of expansions in non-integer bases. The present paper includes an investigation of the reachable workspace, a more general analysis of the control system underlying the model, its reachability and local controllability properties and the relation with expansions in non-integer bases and with iterated function systems

Toray\u27s Touch Roll Manipulator

The goal of Easily Manipulated (EM) is to design and build an apparatus to effectively and efficiently manipulate a touch roll from a cart on the ground to the mounting chucks on a J6 slitter at Toray Plastics. The current process is long and involved, something that Toray is not happy with. EM has worked with the University of Rhode Island (URI) and Toray to come up with a solution that will minimize the amount of time needed to switch out the touch rolls and will only need one operator to make the process more efficient. the design had to satisfy Toray\u27s requirements of being lightweight, structurally sound, non-permanently a fixed to the slitter, and have the ability to be utilized at anytime. The design that EM has created complies with these parameters and also is a simply and easy to use design. The design being used combines a slide and a sleeve concept to be easily mounted to the winder arms on the J6 slitter and provides a bridge over the rotating floor to the mounting chuck. Because this design will be used while the winder arms are in an upright position, and the floor of the slitter rotates with the arms, a single operator will be able to push the touch rolls across the slides directly into the mounting chucks. The slide is fixed on the sleeve to not allow any rotation and maintain the simplicity of the project. The design has gone through multiple iterations and has continued to evolve over the past months. Right now the current build includes a wooden sleeve that has three sides that will fit snuggly around the winder arm, and a slide built out of 80/20 aluminum to demonstrate the overall strength of the design. The concept designed by EM will match the requirements set forth by Toray

Mobile-manipulating UAVs for Sensor Installation, Bridge Inspection and Maintenance

Mobile manipulating UAVs have great potential for bridge inspection and maintenance. Since 2002, the PI has developed UAVs that could fly through in-and-around buildings and tunnels. Collision avoidance in such cluttered near-Earth environments has been a key challenge. The advent of light-weight, computationally powerful cameras led to breakthroughs in SLAM even though SLAM-based autonomous aerial navigation around bridges remains an unsolved problem. In 2007, the PI integrated a mobile manipulation function into UAVs, greatly extending the capabilities of UAVs from passive survey of environments with cameras to active interaction with environments using limbs. Mobile-manipulating UAVs have since been demonstrated to successfully turn valves, install sensors, open doors, and drag ropes. Their research and development face several challenges. First, limbs add weight to aircraft. Second, rotorcraft, like a quadcopter, is an under-actuated system whose stability can be easily affected by limb motions. Third, when performing a task like turning a valve, limbs demand compensation for torque-force interactions. Thus, even if battery technologies afford the additional payload of limbs, current knowledge for manipulation with under-actuated systems remains sparse. This project aims to develop and prototype a mobile-manipulating UAV for bridge maintenance and disaster cleanup through further study on SLAM technology for robust navigation, impedance controllers to ensure UAV’s stability with limb motion, and coordinated and cooperative motions of multiple limbs to perform simple tasks like bearings cleaning and crack sealing in concrete bridges. Two strategies will be explored for bridge maintenance: (a) A UAV brings and uses a can of compressed air for bridge cleaning, and (2) Two UAVs airlift, position, and operate hoses from ground, and clean bridges with air or water. The latter can be potentially implemented by including a station-keeping, lighter-than-air UAV like blimp that can airlift a hose and remain airborne for extended periods. The mobile-limbed UAVs can then pull-and-drag the hose into areas that need to be cleaned. The blimp-based approach is attractive because it is easier for a UAV to drop hose lengths rather than pull the hose up in air

Modeling, simulation and control of microrobots for the microfactory.

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large quantities of components, and the high cost associated with top-down manipulation requiring precision. However, bottom-up manufacturing methods have certain limitations, such as components needing to have predefined shapes and surface coatings, and the number of assembly components being limited to very few. For example, in the case of self-assembly of nano-cubes with an origami design, post-assembly manipulation of cubes in large quantities and cost-efficiency is still challenging. In this thesis, we envision a new paradigm for nanoscale assembly, realized with the help of a wafer-scale microfactory containing large numbers of MEMS microrobots. These robots will work together to enhance the throughput of the factory, while their cost will be reduced when compared to conventional nanopositioners. To fulfill the microfactory vision, numerous challenges related to design, power, control, and nanoscale task completion by these microrobots must be overcome. In this work, we study two classes of microrobots for the microfactory: stationary microrobots and mobile microrobots. For the stationary microrobots in our microfactory application, we have designed and modeled two different types of microrobots, the AFAM (Articulated Four Axes Microrobot) and the SolarPede. The AFAM is a millimeter-size robotic arm working as a nanomanipulator for nanoparticles with four degrees of freedom, while the SolarPede is a light-powered centimeter-size robotic conveyor in the microfactory. For mobile microrobots, we have introduced the world’s first laser-driven micrometer-size locomotor in dry environments, called ChevBot to prove the concept of the motion mechanism. The ChevBot is fabricated using MEMS technology in the cleanroom, following a microassembly step. We showed that it can perform locomotion with pulsed laser energy on a dry surface. Based on the knowledge gained with the ChevBot, we refined tits fabrication process to remove the assembly step and increase its reliability. We designed and fabricated a steerable microrobot, the SerpenBot, in order to achieve controllable behavior with the guidance of a laser beam. Through modeling and experimental study of the characteristics of this type of microrobot, we proposed and validated a new type of deep learning controller, the PID-Bayes neural network controller. The experiments showed that the SerpenBot can achieve closed-loop autonomous operation on a dry substrate