Design and experimental analysis of legged locomotive robots

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 20-21).In this thesis, I present the design and motion-capture analysis of two previously well-studied dynamic-walking machines, the rimless wheel and the compass gait robot. These robots were the basis for my undergraduate research at the Computer Science/Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. The rimless wheel is a real-world physical realization built to compare to a long-analyzed model, the simplest example of passive dynamic walking. Despite the seemingly deterministic model, undeniable experimental evidence for unpredictable stochasitic behavior is observed. The compass gait is the second iteration of a previous design by Dr. Fumiya Iida in my laboratory. Both machines are among the most fundamental walking models, and are important for developing energy-efficient dynamic walkers.by Timothy J. Villabona.S.B

Modeling, system identication, and control for dynamic locomotion of the LittleDog robot on rough terrain

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.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. 76-80).In this thesis, I present a framework for achieving a stable bounding gait on the LittleDog robot over rough terrain. The framework relies on an accurate planar model of the dynamics, which I assembled from a model of the motors, a rigid body model, and a novel physically-inspired ground interaction model, and then identied using a series of physical measurements and experiments. I then used the RG-RRT algorithm on the model to generate bounding trajectories of LittleDog over a number of sets of rough terrain in simulation. Despite signicant research in the field, there has been little success in combining motion planning and feedback control for a problem that is as kinematically and dynamically challenging as LittleDog. I have constructed a controller based on transverse linearization and used it to stabilize the planned LittleDog trajectories in simulation. The resulting controller reliably stabilized the planned bounding motions and was relatively robust to signicant amounts of time delays in estimation, process and estimation noise, as well as small model errors. In order to estimate the state of the system in real time, I modified the EKF algorithm to compensate for varying delays between the sensors. The EKF-based filter works reasonably well, but when combined with feedback control, simulated delays, and the model it produces unstable behavior, which I was not able to correct. However, the close loop simulation closely resembles the behavior of the control and estimation on the real robot, including the failure modes, which suggests that improving the feedback loop might result in bounding on the real LittleDog. The control framework and many of the methods developed in this thesis are applicable to other walking systems, particularly when operating in the underactuated regime.by Michael Yurievich Levashov.S.M

Design, construction, and experiments with a compass gait walking robot

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 91-93).In recent years a number of new computational techniques for the control of nonlinear and underactuated systems have been developed and tested largely in theory and simulation. In order to better understand how these new tools are applied to real systems and to expose areas where the theory is lacking testing on a physical model system is necessary. In this thesis a human scale, free walking, planar bipedal walking robot is designed and several of these new control techniques are tested. These include system identification via simulation error optimization, simulation based LQR-Trees, and transverse stabilization of trajectories. Emphasis is put on the topics of designing highly dynamic robots, practical considerations in implementation of these advanced control strategies, and exploring where these techniques need additional development.by Zachary J Jackowski.S.M

Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain

Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics

Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain

Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics