Modular high maneuverability autonomous underwater vehicle

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Includes bibliographical references (p. 111-115).The design and construction of a modular test bed autonomous underwater vehicle (AUV) is analyzed. Although a relatively common stacked-hull design is used, the state of the art is advanced through an aggressive power plant, with capability to support azimuthing thrusters and a 2DOF front sensor assembly. Through an application of lean principles to developmental hardware, the notion of a delayed differentiation is isolated as a key to minimizing rework and creating essentially transparent electronic hardware. Additionally, the use of bus-modular structural and electronic interconnects facilitates reconfiguration of the vehicle across a large range of components, allowing the rapid development of new sensors, control algorithms, and mechanical hardware. Initial wet tests confirm basic data acquisition capabilities and allowed sensor fusion of scanning sonar returns at the beam level with data from an IMU for an orientation-corrected sonar mosaic.by Daniel G. Walker.S.M

ADAPTIVE SAMPLING METHODS FOR TESTING AUTONOMOUS SYSTEMS

In this dissertation, I propose a software-in-the-loop testing architecture that uses adaptive sampling to generate test suites for intelligent systems based upon identifying transitions in high-level mission criteria. Simulation-based testing depends on the ability to intelligently create test-cases that reveal the greatest information about the performance of the system in the fewest number of runs. To this end, I focus on the discovery and analysis of performance boundaries. Locations in the testing space where a small change in the test configuration leads to large changes in the vehicle's behavior. These boundaries can be used to characterize the regions of stable performance and identify the critical factors that affect autonomous decision making software. By creating meta-models which predict the locations of these boundaries we can efficiently query the system and find informative test scenarios. These algorithms form the backbone of the Range Adversarial Planning Tool (RAPT): a software system used at naval testing facilities to identify the environmental triggers that will cause faults in the safety behavior of unmanned underwater vehicles (UUVs). This system was used to develop UUV field tests which were validated on a hardware platform at the Keyport Naval Testing Facility. The development of test cases from simulation to deployment in the field required new analytical tools. Tools that were capable of handling uncertainty in the vehicle's performance, and the ability to handle large datasets with high-dimensional outputs. This approach has also been applied to the generation of self-righting plans for unmanned ground vehicles (UGVs) using topological transition graphs. In order to create these graphs, I had to develop a set of manifold sampling and clustering algorithms which could identify paths through stable regions of the configuration space. Finally, I introduce an imitation learning approach for generating surrogate models of the target system's control policy. These surrogate agents can be used in place of the true autonomy to enable faster than real-time simulations. These novel tools for experimental design and behavioral modeling provide a new way of analyzing the performance of robotic and intelligent systems, and provide a designer with actionable feedback

Bio-inspired Dynamic Control Systems with Time Delays

The world around us exhibits a rich and ever changing environment of startling, bewildering and fascinating complexity. Almost everything is never as simple as it seems, but through the chaos we may catch fleeting glimpses of the mechanisms within. Throughout the history of human endeavour we have mimicked nature to harness it for our own ends. Our attempts to develop truly autonomous and intelligent machines have however struggled with the limitations of our human ability. This has encouraged some to shirk this responsibility and instead model biological processes and systems to do it for us. This Thesis explores the introduction of continuous time delays into biologically inspired dynamic control systems. We seek to exploit rich temporal dynamics found in physical and biological systems for modelling complex or adaptive behaviour through the artificial evolution of networks to control robots. Throughout, arguments have been presented for the modelling of delays not only to better represent key facets of physical and biological systems, but to increase the computational potential of such systems for the synthesis of control. The thorough investigation of the dynamics of small delayed networks with a wide range of time delays has been undertaken, with a detailed mathematical description of the fixed points of the system and possible oscillatory modes developed to fully describe the behaviour of a single node. Exploration of the behaviour for even small delayed networks illustrates the range of complex behaviour possible and guides the development of interesting solutions. To further exploit the potential of the rich dynamics in such systems, a novel approach to the 3D simulation of locomotory robots has been developed focussing on minimising the computational cost. To verify this simulation tool a simple quadruped robot was developed and the motion of the robot when undergoing a manually designed gait evaluated. The results displayed a high degree of agreement between the simulation and laser tracker data, verifying the accuracy of the model developed. A new model of a dynamic system which includes continuous time delays has been introduced, and its utility demonstrated in the evolution of networks for the solution of simple learning behaviours. A range of methods has been developed for determining the time delays, including the novel concept of representing the time delays as related to the distance between nodes in a spatial representation of the network. The application of these tools to a range of examples has been explored, from Gene Regulatory Networks (GRNs) to robot control and neural networks. The performance of these systems has been compared and contrasted with the efficacy of evolutionary runs for the same task over the whole range of network and delay types. It has been shown that delayed dynamic neural systems are at least as capable as traditional Continuous Time Recurrent Neural Networks (CTRNNs) and show significant performance improvements in the control of robot gaits. Experiments in adaptive behaviour, where there is not such a direct link between the enhanced system dynamics and performance, showed no such discernible improvement. Whilst we hypothesise that the ability of such delayed networks to generate switched pattern generating nodes may be useful in Evolutionary Robotics (ER) this was not borne out here. The spatial representation of delays was shown to be more efficient for larger networks, however these techniques restricted the search to lower complexity solutions or led to a significant falloff as the network structure becomes more complex. This would suggest that for anything other than a simple genotype, the direct method for encoding delays is likely most appropriate. With proven benefits for robot locomotion and the open potential for adaptive behaviour delayed dynamic systems for evolved control remain an interesting and promising field in complex systems research

Snake and Snake Robot Locomotion in Complex, 3-D Terrain

Snakes are able to traverse almost all types of environments by bending their elongate bodies in three dimensions to interact with the terrain. Similarly, a snake robot is a promising platform to perform critical tasks in various environments. Understanding how 3-D body bending effectively interacts with the terrain for propulsion and stability can not only inform how snakes move through natural environments, but also inspire snake robots to achieve similar performance to facilitate humans. How snakes and snake robots move on flat surfaces has been understood relatively well in previous studies. However, such ideal terrain is rare in natural environments and little was understood about how to generate propulsion and maintain stability when large height variations occur, except for some qualitative descriptions of arboreal snake locomotion and a few robots using geometric planning. To bridge this knowledge gap, in this dissertation research we integrated animal experiments and robotic studies in three representative environments: a large smooth step, an uneven arena of blocks of large height variation, and large bumps. We discovered that vertical body bending induces stability challenges but can generate large propulsion. When traversing a large smooth step, a snake robot is challenged by roll instability that increases with larger vertical body bending because of a higher center of mass. The instability can be reduced by body compliance that statistically increases surface contact. Despite the stability challenge, vertical body bending can potentially allow snakes to push against terrain for propulsion similar to lateral body bending, as demonstrated by corn snakes traversing an uneven arena. This ability to generate large propulsion was confirmed on a robot if body-terrain contact is well maintained. Contact feedback control can help the strategy accommodate perturbations such as novel terrain geometry or excessive external forces by helping the body regain lost contact. Our findings provide insights into how snakes and snake robots can use vertical body bending for efficient and versatile traversal of the three-dimensional world while maintaining stability

Self–organised multi agent system for search and rescue operations

Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore an unknown search terrain with complex topology in multiple predefined stages by performing pertinent strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined environments is one of the main challenges for search and rescue robots inside collapsed buildings. In this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform a fast, fair, and thorough search as well as solving the multi–agent traffic congestion. Our simulations have been performed on different test environments in which the complexity of the search field has been defined by fractal dimension of Brownian movements. The exploration stages are depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research is on the red arena with the least structure and most challenging parts to robot nimbleness

The dynamic modelling and development of a controller for a general purpose remotely operated underwater vehicle

A preliminary mathematical model for the UCT SEAHOG Remotely operated underwater vehicle (ROV) is developed, including estimation of the rigid body, hydrodynamic and hydrostatic properties of the robot. A single state thruster model is developed and verified according to real life test data. A closed-loop speed controller is developed for the thruster module using a standard PI scheme and is implemented on an MSP430 microcontroller using software fixed-point algorithms. The complete ROV system is simulated in Simulink® in an open-loop configuration to gain insight into the expected motion from the vehicle. Controllers for depth and heading holding are designed using standard PID linearized control methods with gain scheduling and are then assessed within the complete system in a simulation environment. In addition, upgrades and maintenance are performed on the Power Pod, light and camera modules. Redesign, manufacture and testing of the SEAHOG junction box is performed, including a design solution to connect the tether power and fibre-optic lines at the surface and on the ROV. An extensive overhaul of the SEAHOG GUI is performed, utilising multicore processing architecture in LabVIEW and resulting in a user-orientated interface capable of controlling and monitoring all existing system data from the robot

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

ISMCR 1994: Topical Workshop on Virtual Reality. Proceedings of the Fourth International Symposium on Measurement and Control in Robotics

This symposium on measurement and control in robotics included sessions on: (1) rendering, including tactile perception and applied virtual reality; (2) applications in simulated medical procedures and telerobotics; (3) tracking sensors in a virtual environment; (4) displays for virtual reality applications; (5) sensory feedback including a virtual environment application with partial gravity simulation; and (6) applications in education, entertainment, technical writing, and animation

Continuum Mechanical Models for Design and Characterization of Soft Robots

The emergence of ``soft'' robots, whose bodies are made from stretchable materials, has fundamentally changed the way we design and construct robotic systems. Demonstrations and research show that soft robotic systems can be useful in rehabilitation, medical devices, agriculture, manufacturing and home assistance. Increasing need for collaborative, safe robotic devices have combined with technological advances to create a compelling development landscape for soft robots. However, soft robots are not yet present in medical and rehabilitative devices, agriculture, our homes, and many other human-collaborative and human-interactive applications. This gap between promise and practical implementation exists because foundational theories and techniques that exist in rigid robotics have not yet been developed for soft robots. Theories in traditional robotics rely on rigid body displacements via discrete joints and discrete actuators, while in soft robots, kinematic and actuation functions are blended, leading to nonlinear, continuous deformations rather than rigid body motion. This dissertation addresses the need for foundational techniques using continuum mechanics. Three core questions regarding the use of continuum mechanical models in soft robotics are explored: (1) whether or not continuum mechanical models can describe existing soft actuators, (2) which physical phenomena need to be incorporated into continuum mechanical models for their use in a soft robotics context, and (3) how understanding on continuum mechanical phenomena may form bases for novel soft robot architectures. Theoretical modeling, experimentation, and design prototyping tools are used to explore Fiber-Reinforced Elastomeric Enclosures (FREEs), an often-used soft actuator, and to develop novel soft robot architectures based on auxetic behavior. This dissertation develops a continuum mechanical model for end loading on FREEs. This model connects a FREE’s actuation pressure and kinematic configuration to its end loads by considering stiffness of its elastomer and fiber reinforcement. The model is validated against a large experimental data set and compared to other FREE models used by roboticists. It is shown that the model can describe the FREE’s loading in a generalizable manner, but that it is bounded in its peak performance. Such a model can provide the novel function of evaluating the performance of FREE designs under high loading without the costs of building and testing prototypes. This dissertation further explores the influence viscoelasticity, an inherent property of soft polymers, on end loading of FREEs. The viscoelastic model developed can inform soft roboticists wishing to exploit or avoid hysteresis and force reversal. The final section of the dissertations explores two contrasting styles of auxetic metamaterials for their uses in soft robotic actuation. The first metamaterial architecture is composed of beams with distributed compliance, which are placed antagonistic configurations on a variety of surfaces, giving ride to shape morphing behavior. The second metamaterial architecture studied is a ``kirigami’’ sheet with an orthogonal cut pattern, utilizing lumped compliance and strain hardening to permanently deploy from a compact shape to a functional one. This dissertation lays the foundation for design of soft robots by robust physical models, reducing the need for physical prototypes and trial-and-error approaches. The work presented provides tools for systematic exploration of FREEs under loading in a wide range of configurations. The work further develops new concepts for soft actuators based on continuum mechanical modeling of auxetic metamaterials. The work presented expands the available tools for design and development of soft robotic systems, and the available architectures for soft robot actuation.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163236/1/asedal_1.pd