Design, modelling and control of a brachiating power line inspection robot

The inspection of power lines and associated hardware is vital to ensuring the reliability of the transmission and distribution network. The repetitive nature of the inspection tasks present a unique opportunity for the introduction of robotic platforms, which offer the ability to perform more systematic and detailed inspection than traditional methods. This lends itself to improved asset management automation, cost-effectiveness and safety for the operating crew. This dissertation presents the development of a prototype industrial brachiating robot. The robot is mechanically simple and capable of dynamically negotiating obstacles by brachiating. This is an improvement over current robotic platforms, which employ slow, high power static schemes for obstacle negotiation. Mathematical models of the robot were derived to understand the underlying dynamics of the system. These models were then used in the generation of optimal trajectories, using nonlinear optimisation techniques, for brachiating past line hardware. A physical robot was designed and manufactured to validate the brachiation manoeuvre. The robot was designed following classic mechanical design principles, with emphasis on functional design and robustness. System identification was used to capture the plant uncertainty and a feedback controller was designed to track the reference trajectory allowing for energy optimal brachiation swings. Finally, the robot was tested, starting with sub-system testing and ending with testing of a brachiation manoeuvre proving the prospective viability of the robot in an industrial environment

Estimation and control of flexible space structures for autonomous on-orbit assembly

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009.Includes bibliographical references (p. 135-139).The ability to autonomously assemble large structures in space is desirable for the construction of large orbiting solar arrays, interplanetary spacecraft, or space telescopes. One technique uses free-flying satellites to manipulate and connect elements of the structure. Since these elements are often flexible and lack embedded actuators and sensors, the assembly robot must use its own actuators and onboard measurements to suppress vibrations during transportation maneuvers. This thesis will examine the dynamic modeling of a free-flying robot attached to a flexible beam-like element, vision-based estimation of vibrational motion, and trajectory control for assembly of a space structure.by Jacob G. Katz.S.M

High-dimensional underactuated motion planning via task space control

Abstract — Kinodynamic planning algorithms have the potential to find feasible control trajectories which accomplish a task even in very nonlinear or constrained dynamical systems. Underactuation represents a particular form of a dynamic constraint, inherently present in many machines of interest (e.g., walking robots), and necessitates planning for long-term control solutions. A major limitation in motion planning techniques, especially for real-time implementation, is that they are only practical for relatively low degree-of-freedom problems. Here we present a model-based dimensionality reduction technique based on an extension of partial feedback linearization control into a task-space framework. This allows one to plan motions for a complex underactuated robot directly in a low-dimensional task-space, and to resolve redundancy with lower-priority tasks. We illustrate the potential of this approach with an extremely simple motion planning system which solves the swing-up problem for multi-link underactuated pendula, and discuss extensions to the control of walking. I

Understanding the motions of the cheetah tail using robotics

The cheetah is capable of incredible feats of manoeuvrability. But, what is interesting about these manoeuvres is that they involve rapid swinging of the animal's lengthy tail. Despite this, very little is understood about the cheetah tail and its motion, with the common view being that it is "heavy" and possibly used as a "counter balance" or as a "rudder". In this dissertation, this subject is investigated by exploring the motions of the cheetah tail by means of mathematic al models, feedback control and novel robot platforms. Particularly, the motion in the roll axis is first investigated and it is determined that it assists stability of high speed turns. This is validated by modelling and experimental testing on a novel tailed robot, Dima I. Inspired by cheetah video observations, the tail motion in the pitch axis during rapid acceleration and braking manoeuvres is also investigated. Once again modelling and experimental testing on a tailed robot are performed and the tail is shown to stabilise rapid acceleration manoeuvres. Video observations also indicate the tail movement in the shape of a cone: a combination of pitching and yawing. Understanding this motion is done by setting up an optimization problem. Here, the optimal motion was found to be to a cone which results in a continuous torque on the body during a turn while galloping. A novel two degree of freedom tailed robot, Dima II, was then developed to experimentally validate the effect of this motion. Lastly, measurement of the cheetah tail inertia was performed during a routine necropsy where it was found to have lower inertia than assumed. However, the tail has thick, long fur that was tested in a wind tunnel. Here it was found that the furry tail is capable of producing significant drag forces without a weight penalty. Subsequently, mathematical models incorporating the aerodynamics of the tail were developed and these were used to demonstrate its effectiveness during manoeuvres

Sample-based motion planning in high-dimensional and differentially-constrained systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 115-124).State of the art sample-based path planning algorithms, such as the Rapidly-exploring Random Tree (RRT), have proven to be effective in path planning for systems subject to complex kinematic and geometric constraints. The performance of these algorithms, however, degrade as the dimension of the system increases. Furthermore, sample-based planners rely on distance metrics which do not work well when the system has differential constraints. Such constraints are particularly challenging in systems with non-holonomic and underactuated dynamics. This thesis develops two intelligent sampling strategies to help guide the search process. To reduce sensitivity to dimension, sampling can be done in a low-dimensional task space rather than in the high-dimensional state space. Altering the sampling strategy in this way creates a Voronoi Bias in task space, which helps to guide the search, while the RRT continues to verify trajectory feasibility in the full state space. Fast path planning is demonstrated using this approach on a 1500-link manipulator. To enable task-space biasing for underactuated systems, a hierarchical task space controller is developed by utilizing partial feedback linearization. Another sampling strategy is also presented, where the local reachability of the tree is approximated, and used to bias the search, for systems subject to differential constraints. Reachability guidance is shown to improve search performance of the RRT by an order of magnitude when planning on a pendulum and non-holonomic car. The ideas of task-space biasing and reachability guidance are then combined for demonstration of a motion planning algorithm implemented on LittleDog, a quadruped robot. The motion planning algorithm successfully planned bounding trajectories over extremely rough terrain.by Alexander C. Shkolnik.Ph.D

Upravljački algoritam za podupravljane mehaničke sustave s uključenom dinamikom pogona

U ovom radu izvodi se opći upravljački algoritam za istodobno stabiliziranje i praćenje trajektorija podupravljanih nelinearnih mehaničkih sustava (UNMS) s električnim, pneumatskim i hidrauličkim pogonima (aktuatorima). Istodobna stabilizacija i praćenje trajektorija odnosi se na stupnjeve slobode gibanja sustava, a obuhvaćaju se neholonomni sustavi drugog reda i sustavi sa spregom ulaznih veličina. Algoritam rješava probleme koji nastaju zbog podupravljanosti, zanemarivanja dinamike pogona i zanemarivanja statičkog trenja. S njim su poboljšane značajke zatvorenog upravljačkog kruga u odnosu na sustave sa zanemarenom dinamikom pogona i/ili zanemarenim statičkim trenjem kakvi se često koriste. Rješavanje ovakvih problema zahtijeva upravljačke algoritme temeljene na regulatorima s promjenjivom strukturom. Matematička jednostavnost novo uvedenog algoritma omogućuje laku ugradnju u računalne programe, pa je algoritam pogodan za realizaciju u praksi. Značaj ovog istraživanja leži u upravljačkom zakonu koji svojom uporabom omogućuje upravljanje proizvoljno odabranim stupnjevima slobode gibanja sustava s ciljem zadovoljenja kvalitativnih značajki regulacije. To rezultira stabilnim i robusnim ponašanjem podupravljanih sustava