Path and Motion Planning for Autonomous Mobile 3D Printing

Autonomous robotic construction was envisioned as early as the ‘90s, and yet, con- struction sites today look much alike ones half a century ago. Meanwhile, highly automated and efficient fabrication methods like Additive Manufacturing, or 3D Printing, have seen great success in conventional production. However, existing efforts to transfer printing technology to construction applications mainly rely on manufacturing-like machines and fail to utilise the capabilities of modern robotics. This thesis considers using Mobile Manipulator robots to perform large-scale Additive Manufacturing tasks. Comprised of an articulated arm and a mobile base, Mobile Manipulators, are unique in their simultaneous mobility and agility, which enables printing-in-motion, or Mobile 3D Printing. This is a 3D printing modality, where a robot deposits material along larger-than-self trajectories while in motion. Despite profound potential advantages over existing static manufacturing-like large- scale printers, Mobile 3D printing is underexplored. Therefore, this thesis tack- les Mobile 3D printing-specific challenges and proposes path and motion planning methodologies that allow this printing modality to be realised. The work details the development of Task-Consistent Path Planning that solves the problem of find- ing a valid robot-base path needed to print larger-than-self trajectories. A motion planning and control strategy is then proposed, utilising the robot-base paths found to inform an optimisation-based whole-body motion controller. Several Mobile 3D Printing robot prototypes are built throughout this work, and the overall path and motion planning strategy proposed is holistically evaluated in a series of large-scale 3D printing experiments

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Planning and control for microassembly of structures composed of stress-engineered MEMS microrobots

We present control strategies that implement planar microassembly using groups of stress-engineered MEMS microrobots (MicroStressBots) controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. In order for the robots to assemble into arbitrary planar shapes despite the high degree of underactuation, it is desirable that each robot be independently maneuverable (independently controllable). To achieve independent control, we fabricated robots that behave (move) differently from one another in response to the same global control signal. We harnessed this differentiation to develop assembly control strategies, where the assembly goal is a desired geometric shape that can be obtained by connecting the chassis of individual robots. We derived and experimentally tested assembly plans that command some of the robots to make progress toward the goal, while other robots are constrained to remain in small circular trajectories (orbits) until it is their turn to move into the goal shape. Our control strategies were tested on systems of fabricated MicroStressBots. The robots are 240–280 µm × 60 µm × 7–20 µm in size and move simultaneously within a single operating environment. We demonstrated the feasibility of our control scheme by accurately assembling five different types of planar microstructures

Nonlinear control and synchronization of multiple Lagrangian systems with application to tethered formation flight spacecraft

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 217-228).This dissertation focuses on the synchronization of multiple dynamical systems using contraction theory, with applications to cooperative control of multi-agent systems and synchronization of interconnected dynamics such as tethered formation flight. Inspired by stable combinations of biological systems, contraction nonlinear stability theory provides a systematic method to reduce arbitrarily complex systems into simpler elements. One application of oscillation synchronization is a fully decentralized nonlinear control law, which eliminates the need for any inter-satellite communications. We use contraction theory to prove that a nonlinear control law stabilizing a single-tethered spacecraft can also stabilize arbitrarily large circular arrays of tethered spacecraft, as well as a three-spacecraft inline configuration. The convergence result is global and exponential due to the nature of contraction analysis. The proposed decentralized control strategy is further extended to robust adaptive control in order to account for model uncertainties. Numerical simulations and experimental results validate the exponential stability of the tethered formation arrays by implementing a tracking control law derived from the reduced dynamics.(cont.) This thesis also presents a new synchronization framework that can be directly applied to cooperative control of autonomous aerospace vehicles and oscillation synchronization in robotic manipulation and locomotion. We construct a dynamical network of multiple Lagrangian systems by adding diffusive couplings to otherwise freely moving or flying vehicles. The proposed tracking control law synchronizes an arbitrary number of robots into a common trajectory with global exponential convergence. The proposed control law is much simpler than earlier work in terms of both the computational load and the required signals. Furthermore, in contrast with earlier work which used simple double integrator models, the proposed method permits highly nonlinear systems and is further extended to adaptive synchronization, partial-joint coupling, and concurrent synchronization. Another contribution of the dissertation is a novel nonlinear control approach for underactuated tethered formation flight spacecraft. This is motivated by a controllability analysis that indicates that both array resizing and spin-up are fully controllable by the reaction wheels and the tether motor. This work reports the first propellant-free underactuated control results for tethered formation flight.(cont.) We also fulfill the potential of the proposed strategy by providing a new momentum dumping method. This dissertation work has evolved based on the research philosophy of balancing theoretical work with practicality, aiming at physically intuitive algorithms that can be directly implemented in real systems. In order to validate the effectiveness of the decentralized control and estimation framework, a new suite of hardware has been designed and added to the SPHERES (Synchronize Position Hold Engage and Reorient Experimental Satellite) testbed. Such recent improvements described in this dissertation include a new tether reel mechanism, a force-torque sensor and an air-bearing carriage with a reaction wheel. This thesis also introduces a novel relative attitude estimator, in which a series of Kalman filters incorporate the gyro, force-torque sensor and ultrasound ranging measurements. The closed-loop control experiments can be viewed at ...by Soon-Jo Chung.Sc.D