Engineering topics

SunSpiral, Vytas

Publications and source records attributed to SunSpiral, Vytas.

14 records

NASA NTRS2018

Super Ball Bot - Structures for Planetary Landing and Exploration

Small, light-weight and low-cost missions will become increasingly important to NASA's exploration goals for our solar system. Ideally teams of dozens or even hundreds of small, collapsable robots, weighing only a few kilograms a piece, will be conveniently packed during launch and would reliably separate and unpack at their destination. Such teams will allow rapid, reliable in-situ exploration of hazardous destination such as Titan, where imprecise terrain knowledge and unstable precipitation cycles make single-robot exploration problematic. Unfortunately landing many lightweight conventional robots is difficult with conventional technology. Current robot designs are delicate, requiring combinations of devices such as parachutes, retrorockets and impact balloons to minimize impact forces and to place a robot in a proper orientation. Instead we propose to develop a radically different robot based on a "tensegrity" built purely upon tensile and compression elements. These robots can be light-weight, absorb strong impacts, are redundant against single-point failures, can recover from different landing orientations and are easy to collapse and uncollapse. We believe tensegrity robot technology can play a critical role in future planetary exploration.

Agogino, Adrian K.↗

NASA NTRS2016

3D Robot User Interfaces

Presentation that summarizes the 3D robot user interfaces developed by the ARC Intelligent Robotics Group.

robotics↗

NASA NTRS2015

Super Ball Bot - Structures for Planetary Landing and Exploration, NIAC Phase 2 Final Report

Small, light-weight and low-cost missions will become increasingly important to NASA's exploration goals. Ideally teams of small, collapsible, light weight robots, will be conveniently packed during launch and would reliably separate and unpack at their destination. Such robots will allow rapid, reliable in-situ exploration of hazardous destination such as Titan, where imprecise terrain knowledge and unstable precipitation cycles make single-robot exploration problematic. Unfortunately landing lightweight conventional robots is difficult with current technology. Current robot designs are delicate, requiring a complex combination of devices such as parachutes, retrorockets and impact balloons to minimize impact forces and to place a robot in a proper orientation. Instead we are developing a radically different robot based on a "tensegrity" structure and built purely with tensile and compression elements. Such robots can be both a landing and a mobility platform allowing for dramatically simpler mission profile and reduced costs. These multi-purpose robots can be light-weight, compactly stored and deployed, absorb strong impacts, are redundant against single-point failures, can recover from different landing orientations and can provide surface mobility. These properties allow for unique mission profiles that can be carried out with low cost and high reliability and which minimizes the inefficient dependance on "use once and discard" mass associated with traditional landing systems. We believe tensegrity robot technology can play a critical role in future planetary exploration.

Tensegrity↗

NASA NTRS2014

Impedance Controlled Twisted String Actuators for Tensegrity Robots

We are developing impedance controlled twisted string actuators (TSA) for use in tensegrity robots, as an alternative to traditional spooled cable actuation. Tensegrity robots are composed of continuous tension and discontinuous compression elements, with no rigid joints between elements, which give them unique force distribution properties. The use of tensegrity robots is strongly motivated by biological examples, and they are capable of locomotion and manipulation by changing lengths of their continuous network of tensional elements, which is also the primary pathways for load transfer through the structure. TSA show the potential to address some of the unique engineering challenges faced by tensegrity structures, and provide unique qualities well suited to an actively controlled tension system, such as compact, light-weight mechanical structures, inherent compliance, variable gearing'', and the ability to transmit high forces with a very low input torque. The inherent variable compliance of impedance control is essential for tensegrity robots to move through and manipulate the environment, and is a natural match to the unique qualities of TSA. This paper briefly introduces the tensegrity robots in the NASA Ames Intelligent Robotics Group and an overview of their future application to space planetary exploration. Then the effectiveness and robustness of TSA are verified through the performance of impedance control modes.

Park, In-Won↗

NASA NTRS2014

Hardware Design and Testing of SUPERball, A Modular Tensegrity Robot

We are developing a system of modular, autonomous "tensegrity end-caps" to enable the rapid exploration of untethered tensegrity robot morphologies and functions. By adopting a self-contained modular approach, different end-caps with various capabilities (such as peak torques, or motor speeds), can be easily combined into new tensegrity robots composed of rods, cables, and actuators of different scale (such as in length, mass, peak loads, etc). As a first step in developing this concept, we are in the process of designing and testing the end-caps for SUPERball (Spherical Underactuated Planetary Exploration Robot), a project at the Dynamic Tensegrity Robotics Lab (DTRL) within NASA Ames's Intelligent Robotics Group. This work discusses the evolving design concepts and test results that have gone into the structural, mechanical, and sensing aspects of SUPERball. This representative tensegrity end-cap design supports robust and repeatable untethered mobility tests of the SUPERball, while providing high force, high displacement actuation, with a low-friction, compliant cabling system.

Tensegrity↗

NASA NTRS2014

Design and Control of Modular Spine-Like Tensegrity Structures

We present a methodology enabled by the NASA Tensegrity Robotics Toolkit (NTRT) for the rapid structural design of tensegrity robots in simulation and an approach for developing control systems using central pattern generators, local impedance controllers, and parameter optimization techniques to determine effective locomotion strategies for the robot. Biomimetic tensegrity structures provide advantageous properties to robotic locomotion and manipulation tasks, such as their adaptability and force distribution properties, flexibility, energy efficiency, and access to extreme terrains. While strides have been made in designing insightful static biotensegrity structures, gaining a clear understanding of how a particular structure can efficiently move has been an open problem. The tools in the NTRT enable the rapid exploration of the dynamics of a given morphology, and the links between structure, controllability, and resulting gait efficiency. To highlight the effectiveness of the NTRT at this exploration of morphology and control, we will provide examples from the designs and locomotion of four different modular spine-like tensegrity robots.

Modular↗

NASA NTRS2014

Design and Evolution of a Modular Tensegrity Robot Platform

NASA Ames Research Center is developing a compliant modular tensegrity robotic platform for planetary exploration. In this paper we present the design and evolution of the platform's main hardware component, an untethered, robust tensegrity strut, with rich sensor feedback and cable actuation. Each strut is a complete robot, and multiple struts can be combined together to form a wide range of complex tensegrity robots. Our current goal for the tensegrity robotic platform is the development of SUPERball, a 6-strut icosahedron underactuated tensegrity robot aimed at dynamic locomotion for planetary exploration rovers and landers, but the aim is for the modular strut to enable a wide range of tensegrity morphologies. SUPERball is a second generation prototype, evolving from the tensegrity robot ReCTeR, which is also a modular, lightweight, highly compliant 6-strut tensegrity robot that was used to validate our physics based NASA Tensegrity Robot Toolkit (NTRT) simulator. Many hardware design parameters of the SUPERball were driven by locomotion results obtained in our validated simulator. These evolutionary explorations helped constrain motor torque and speed parameters, along with strut and string stress. As construction of the hardware has finalized, we have also used the same evolutionary framework to evolve controllers that respect the built hardware parameters.

Exploration↗

NASA NTRS2013

Controlling Tensegrity Robots Through Evolution

Tensegrity structures (built from interconnected rods and cables) have the potential to offer a revolutionary new robotic design that is light-weight, energy-efficient, robust to failures, capable of unique modes of locomotion, impact tolerant, and compliant (reducing damage between the robot and its environment). Unfortunately robots built from tensegrity structures are difficult to control with traditional methods due to their oscillatory nature, nonlinear coupling between components and overall complexity. Fortunately this formidable control challenge can be overcome through the use of evolutionary algorithms. In this paper we show that evolutionary algorithms can be used to efficiently control a ball-shaped tensegrity robot. Experimental results performed with a variety of evolutionary algorithms in a detailed soft-body physics simulator show that a centralized evolutionary algorithm performs 400 percent better than a hand-coded solution, while the multi-agent evolution performs 800 percent better. In addition, evolution is able to discover diverse control solutions (both crawling and rolling) that are robust against structural failures and can be adapted to a wide range of energy and actuation constraints. These successful controls will form the basis for building high-performance tensegrity robots in the near future.

Robot↗

NASA NTRS2011

Development and Field Testing of the FootFall Planning System for the ATHLETE Robots

The FootFall Planning System is a ground-based planning and decision support system designed to facilitate the control of walking activities for the ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) family of robots. ATHLETE was developed at NASA's Jet Propulsion Laboratory (JPL) and is a large six-legged robot designed to serve multiple roles during manned and unmanned missions to the Moon; its roles include transportation, construction and exploration. Over the four years from 2006 through 2010 the FootFall Planning System was developed and adapted to two generations of the ATHLETE robots and tested at two analog field sites (the Human Robotic Systems Project's Integrated Field Test at Moses Lake, Washington, June 2008, and the Desert Research and Technology Studies (D-RATS), held at Black Point Lava Flow in Arizona, September 2010). Having 42 degrees of kinematic freedom, standing to a maximum height of just over 4 meters, and having a payload capacity of 450 kg in Earth gravity, the current version of the ATHLETE robot is a uniquely complex system. A central challenge to this work was the compliance of the high-DOF (Degree Of Freedom) robot, especially the compliance of the wheels, which affected many aspects of statically-stable walking. This paper will review the history of the development of the FootFall system, sharing design decisions, field test experiences, and the lessons learned concerning compliance and self-awareness.

SunSpiral, Vytas↗

NASA NTRS2010

Optimized Algorithms for Prediction Within Robotic Tele-Operative Interfaces

Robonaut, the humanoid robot developed at the Dexterous Robotics Labo ratory at NASA Johnson Space Center serves as a testbed for human-rob ot collaboration research and development efforts. One of the recent efforts investigates how adjustable autonomy can provide for a safe a nd more effective completion of manipulation-based tasks. A predictiv e algorithm developed in previous work was deployed as part of a soft ware interface that can be used for long-distance tele-operation. In this work, Hidden Markov Models (HMM?s) were trained on data recorded during tele-operation of basic tasks. In this paper we provide the d etails of this algorithm, how to improve upon the methods via optimization, and also present viable alternatives to the original algorithmi c approach. We show that all of the algorithms presented can be optim ized to meet the specifications of the metrics shown as being useful for measuring the performance of the predictive methods. 1

Martin, Rodney A.↗

NASA NTRS2008

ATHLETE's Feet: Mu1ti-Resolution Planning for a Hexapod Robot

ATHLETE is a large six-legged tele-operated robot. Each foot is a wheel; travel can be achieved by walking, rolling, or some combination of the two. Operators control ATHLETE by selecting parameterized commands from a command dictionary. While rolling can be done efficiently with a single command, any motion involving steps is cumbersome - walking a few meters through difficult terrain can take hours. Our goal is to improve operator efficiency by automatically generating sequences of motion commands. There is increasing uncertainty regarding ATHLETE s actual configuration over time and decreasing quality of terrain data farther away from the current position. This, combined with the complexity that results from 36 degrees of kinematic freedom, led to an architecture that interleaves planning and execution at multiple levels, ranging from traditional configuration space motion planning algorithms for immediate moves to higher level task and path planning algorithms for overall travel. The modularity of the architecture also simplifies the development process and allows the operator to interact with and control the system at varying levels of autonomy depending on terrain and need.

Smith, Tristan B.↗

NASA NTRS2008

FootFall: A Ground Based Operations Toolset Enabling Walking for the ATHLETE Rover

The ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) vehicle consists of six identical, six degree of freedom limbs. FootFall is a ground tool for ATHLETE intended to provide an operator with integrated situational awareness, terrain reconstruction, stability and safety analysis, motion planning, and decision support capabilities to enable the efficient generation of flight software command sequences for walking. FootFall has been under development at NASA Ames for the last year, and having accomplished the initial integration, it is being used to generate command sequences for single footfalls. In this paper, the architecture of FootFall in its current state will be presented, results from the recent Human Robotic Systems Project?s Integrated Field Test (Moses Lake, Washington, June, 2008) will be discussed, and future plans for extending the capabilities of FootFall to enable ATHLETE to walk across a boulder field in real time will be described.

SunSpiral, Vytas↗

NASA NTRS2006

Optimized Algorithms for Prediction within Robotic Tele-Operative Interfaces

Robonaut, the humanoid robot developed at the Dexterous Robotics Laboratory at NASA Johnson Space Center serves as a testbed for human-robot collaboration research and development efforts. One of the primary efforts investigates how adjustable autonomy can provide for a safe and more effective completion of manipulation-based tasks. A predictive algorithm developed in previous work was deployed as part of a software interface that can be used for long-distance tele-operation. In this paper we provide the details of this algorithm, how to improve upon the methods via optimization, and also present viable alternatives to the original algorithmic approach. We show that all of the algorithms presented can be optimized to meet the specifications of the metrics shown as being useful for measuring the performance of the predictive methods. Judicious feature selection also plays a significant role in the conclusions drawn.

Martin, Rodney A.↗

NASA NTRS2006

Modeling and Classifying Six-Dimensional Trajectories for Teleoperation Under a Time Delay

Within the context of teleoperating the JSC Robonaut humanoid robot under 2-10 second time delays, this paper explores the technical problem of modeling and classifying human motions represented as six-dimensional (position and orientation) trajectories. A dual path research agenda is reviewed which explored both deterministic approaches and stochastic approaches using Hidden Markov Models. Finally, recent results are shown from a new model which represents the fusion of these two research paths. Questions are also raised about the possibility of automatically generating autonomous actions by reusing the same predictive models of human behavior to be the source of autonomous control. This approach changes the role of teleoperation from being a stand-in for autonomy into the first data collection step for developing generative models capable of autonomous control of the robot.

SunSpiral, Vytas↗