Underwater communication via compact mechanical sound generation

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (page 55).Effective communication with underwater remotely operated vehicles (UROV) can be difficult to accomplish. In water, simple radio communication is quickly dissipated at higher frequencies and lower frequencies require a large antenna, which may not be practical in all applications. Light can also be used to communicate with the vehicles, but requires line of sight between the source and detector. Sound can also be used as a communication method, and has many advantages. It can propagate long distances underwater and does not require line of sight to work effectively. However, generating sound electronically underwater requires a large power speaker to produce tones loud enough to travel far distances. Generating sound mechanically can take advantage of physical resonance and produce high intensity tones in a compact device with a relatively low power input. This can allow for a compact, high intensity method to communicate with remotely operated underwater vehicles.by Wyatt Ubellacker.S.B

Probabilistic Guarantees for Nonlinear Safety-Critical Optimal Control

Leveraging recent developments in black-box risk-aware verification, we provide three algorithms that generate probabilistic guarantees on (1) optimality of solutions, (2) recursive feasibility, and (3) maximum controller runtimes for general nonlinear safety-critical finite-time optimal controllers. These methods forego the usual (perhaps) restrictive assumptions required for typical theoretical guarantees, e.g. terminal set calculation for recursive feasibility in Nonlinear Model Predictive Control, or convexification of optimal controllers to ensure optimality. Furthermore, we show that these methods can directly be applied to hardware systems to generate controller guarantees on their respective systems

Safety-Critical Controller Verification via Sim2Real Gap Quantification

The well-known quote from George Box states that: "All models are wrong, but some are useful." To develop more useful models, we quantify the inaccuracy with which a given model represents a system of interest, so that we may leverage this quantity to facilitate controller synthesis and verification. Specifically, we develop a procedure that identifies a sim2real gap that holds with a minimum probability. Augmenting the nominal model with our identified sim2real gap produces an uncertain model which we prove is an accurate representor of system behavior. We leverage this uncertain model to synthesize and verify a controller in simulation using a probabilistic verification approach. This pipeline produces controllers with an arbitrarily high probability of realizing desired safe behavior on system hardware without requiring hardware testing except for those required for sim2real gap identification. We also showcase our procedure working on two hardware platforms - the Robotarium and a quadruped

Verifying Safe Transitions between Dynamic Motion Primitives on Legged Robots

Functional autonomous systems often realize complex tasks by utilizing state machines comprised of discrete primitive behaviors and transitions between these behaviors. This architecture has been widely studied in the context of quasi-static and dynamics-independent systems. However, applications of this concept to dynamical systems are relatively sparse, despite extensive research on individual dynamic primitive behaviors, which we refer to as "motion primitives." This paper formalizes a process to determine dynamic-state aware conditions for transitions between motion primitives in the context of safety. The result is framed as a "motion primitive graph" that can be traversed by standard graph search and planning algorithms to realize functional autonomy. To demonstrate this framework, dynamic motion primitives -- including standing up, walking, and jumping -- and the transitions between these behaviors are experimentally realized on a quadrupedal robot

Real-time quadruped gait controller for rough terrain locomotion

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 47-48).In disaster situations, humanoid robots offer many advantages as first responders, but must often navigate rough and unstable terrain. The high center of mass and small support polygon of humanoids creates a difficult locomotion challenge. However, a humanoid that can transform into a quadruped for locomotion, such as MIT Biomimetic Robotics Lab's HERMES, adds the stability of a four-legged gait to safely traverse this dangerous landscape. This thesis investigates a trotting gait controller for use on HERMES specifically on rough terrain. The method takes advantage of simpler underlying dynamics of trotting stability to create a robust controller that performs without specific knowledge of the terrain or preplanning steps. Force and moment balance are conducted around the center of mass of the robot and ground reaction forces from the feet. Stance legs stabilize against disturbances in pitch, roll, and center of mass height. Swing legs attempt to land in the optimal position using a ZMP technique, and the gait cycle time is modulated to achieve stability irrespective of the foot placement constrained by the actual terrain. The controller was simulated on the HERMES humanoid robot using randomized terrain and the performance of the controller was investigated.by Wyatt Lee Ubellacker.S.M