2,690 research outputs found
Fast Damage Recovery in Robotics with the T-Resilience Algorithm
Damage recovery is critical for autonomous robots that need to operate for a
long time without assistance. Most current methods are complex and costly
because they require anticipating each potential damage in order to have a
contingency plan ready. As an alternative, we introduce the T-resilience
algorithm, a new algorithm that allows robots to quickly and autonomously
discover compensatory behaviors in unanticipated situations. This algorithm
equips the robot with a self-model and discovers new behaviors by learning to
avoid those that perform differently in the self-model and in reality. Our
algorithm thus does not identify the damaged parts but it implicitly searches
for efficient behaviors that do not use them. We evaluate the T-Resilience
algorithm on a hexapod robot that needs to adapt to leg removal, broken legs
and motor failures; we compare it to stochastic local search, policy gradient
and the self-modeling algorithm proposed by Bongard et al. The behavior of the
robot is assessed on-board thanks to a RGB-D sensor and a SLAM algorithm. Using
only 25 tests on the robot and an overall running time of 20 minutes,
T-Resilience consistently leads to substantially better results than the other
approaches
Robots that can adapt like animals
As robots leave the controlled environments of factories to autonomously
function in more complex, natural environments, they will have to respond to
the inevitable fact that they will become damaged. However, while animals can
quickly adapt to a wide variety of injuries, current robots cannot "think
outside the box" to find a compensatory behavior when damaged: they are limited
to their pre-specified self-sensing abilities, can diagnose only anticipated
failure modes, and require a pre-programmed contingency plan for every type of
potential damage, an impracticality for complex robots. Here we introduce an
intelligent trial and error algorithm that allows robots to adapt to damage in
less than two minutes, without requiring self-diagnosis or pre-specified
contingency plans. Before deployment, a robot exploits a novel algorithm to
create a detailed map of the space of high-performing behaviors: This map
represents the robot's intuitions about what behaviors it can perform and their
value. If the robot is damaged, it uses these intuitions to guide a
trial-and-error learning algorithm that conducts intelligent experiments to
rapidly discover a compensatory behavior that works in spite of the damage.
Experiments reveal successful adaptations for a legged robot injured in five
different ways, including damaged, broken, and missing legs, and for a robotic
arm with joints broken in 14 different ways. This new technique will enable
more robust, effective, autonomous robots, and suggests principles that animals
may use to adapt to injury
Technical Report on: Tripedal Dynamic Gaits for a Quadruped Robot
A vast number of applications for legged robots entail tasks in complex,
dynamic environments. But these environments put legged robots at high risk for
limb damage. This paper presents an empirical study of fault tolerant dynamic
gaits designed for a quadrupedal robot suffering from a single, known
``missing'' limb. Preliminary data suggests that the featured gait controller
successfully anchors a previously developed planar monopedal hopping template
in the three-legged spatial machine. This compositional approach offers a
useful and generalizable guide to the development of a wider range of tripedal
recovery gaits for damaged quadrupedal machines.Comment: Updated *increased font size on figures 2-6 *added a legend, replaced
text with colors in figure 5a and 6a *made variables representing vectors
boldface in equations 8-10 *expanded on calculations in equations 8-10 by
adding additional lines *added a missing "2" to equation 8 (typo) *added mass
of the robot to tables II and III *increased the width of figures 1 and
Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack
Field Programmable Gate Array (FPGA) devices offer a suitable platform for survivable hardware architectures in mission-critical systems. In this dissertation, active dynamic redundancy-based fault-handling techniques are proposed which exploit the dynamic partial reconfiguration capability of SRAM-based FPGAs. Self-adaptation is realized by employing reconfiguration in detection, diagnosis, and recovery phases. To extend these concepts to semiconductor aging and process variation in the deep submicron era, resilient adaptable processing systems are sought to maintain quality and throughput requirements despite the vulnerabilities of the underlying computational devices. A new approach to autonomous fault-handling which addresses these goals is developed using only a uniplex hardware arrangement. It operates by observing a health metric to achieve Fault Demotion using Recon- figurable Slack (FaDReS). Here an autonomous fault isolation scheme is employed which neither requires test vectors nor suspends the computational throughput, but instead observes the value of a health metric based on runtime input. The deterministic flow of the fault isolation scheme guarantees success in a bounded number of reconfigurations of the FPGA fabric. FaDReS is then extended to the Priority Using Resource Escalation (PURE) online redundancy scheme which considers fault-isolation latency and throughput trade-offs under a dynamic spare arrangement. While deep-submicron designs introduce new challenges, use of adaptive techniques are seen to provide several promising avenues for improving resilience. The scheme developed is demonstrated by hardware design of various signal processing circuits and their implementation on a Xilinx Virtex-4 FPGA device. These include a Discrete Cosine Transform (DCT) core, Motion Estimation (ME) engine, Finite Impulse Response (FIR) Filter, Support Vector Machine (SVM), and Advanced Encryption Standard (AES) blocks in addition to MCNC benchmark circuits. A iii significant reduction in power consumption is achieved ranging from 83% for low motion-activity scenes to 12.5% for high motion activity video scenes in a novel ME engine configuration. For a typical benchmark video sequence, PURE is shown to maintain a PSNR baseline near 32dB. The diagnosability, reconfiguration latency, and resource overhead of each approach is analyzed. Compared to previous alternatives, PURE maintains a PSNR within a difference of 4.02dB to 6.67dB from the fault-free baseline by escalating healthy resources to higher-priority signal processing functions. The results indicate the benefits of priority-aware resiliency over conventional redundancy approaches in terms of fault-recovery, power consumption, and resource-area requirements. Together, these provide a broad range of strategies to achieve autonomous recovery of reconfigurable logic devices under a variety of constraints, operating conditions, and optimization criteria
Reset-free Trial-and-Error Learning for Robot Damage Recovery
The high probability of hardware failures prevents many advanced robots
(e.g., legged robots) from being confidently deployed in real-world situations
(e.g., post-disaster rescue). Instead of attempting to diagnose the failures,
robots could adapt by trial-and-error in order to be able to complete their
tasks. In this situation, damage recovery can be seen as a Reinforcement
Learning (RL) problem. However, the best RL algorithms for robotics require the
robot and the environment to be reset to an initial state after each episode,
that is, the robot is not learning autonomously. In addition, most of the RL
methods for robotics do not scale well with complex robots (e.g., walking
robots) and either cannot be used at all or take too long to converge to a
solution (e.g., hours of learning). In this paper, we introduce a novel
learning algorithm called "Reset-free Trial-and-Error" (RTE) that (1) breaks
the complexity by pre-generating hundreds of possible behaviors with a dynamics
simulator of the intact robot, and (2) allows complex robots to quickly recover
from damage while completing their tasks and taking the environment into
account. We evaluate our algorithm on a simulated wheeled robot, a simulated
six-legged robot, and a real six-legged walking robot that are damaged in
several ways (e.g., a missing leg, a shortened leg, faulty motor, etc.) and
whose objective is to reach a sequence of targets in an arena. Our experiments
show that the robots can recover most of their locomotion abilities in an
environment with obstacles, and without any human intervention.Comment: 18 pages, 16 figures, 3 tables, 6 pseudocodes/algorithms, video at
https://youtu.be/IqtyHFrb3BU, code at
https://github.com/resibots/chatzilygeroudis_2018_rt
Engineering Resilient Space Systems
Several distinct trends will influence space exploration missions in the next decade. Destinations are
becoming more remote and mysterious, science questions more sophisticated, and, as mission experience
accumulates, the most accessible targets are visited, advancing the knowledge frontier to more difficult,
harsh, and inaccessible environments. This leads to new challenges including: hazardous conditions that
limit mission lifetime, such as high radiation levels surrounding interesting destinations like Europa or
toxic atmospheres of planetary bodies like Venus; unconstrained environments with navigation hazards,
such as free-floating active small bodies; multielement missions required to answer more sophisticated
questions, such as Mars Sample Return (MSR); and long-range missions, such as Kuiper belt exploration,
that must survive equipment failures over the span of decades. These missions will need to be successful
without a priori knowledge of the most efficient data collection techniques for optimum science return.
Science objectives will have to be revised âon the flyâ, with new data collection and navigation decisions
on short timescales.
Yet, even as science objectives are becoming more ambitious, several critical resources remain
unchanged. Since physics imposes insurmountable light-time delays, anticipated improvements to the
Deep Space Network (DSN) will only marginally improve the bandwidth and communications cadence to
remote spacecraft. Fiscal resources are increasingly limited, resulting in fewer flagship missions, smaller
spacecraft, and less subsystem redundancy. As missions visit more distant and formidable locations, the
job of the operations team becomes more challenging, seemingly inconsistent with the trend of shrinking
mission budgets for operations support. How can we continue to explore challenging new locations
without increasing risk or system complexity?
These challenges are present, to some degree, for the entire Decadal Survey mission portfolio, as
documented in Vision and Voyages for Planetary Science in the Decade 2013â2022 (National Research
Council, 2011), but are especially acute for the following mission examples, identified in our recently
completed KISS Engineering Resilient Space Systems (ERSS) study:
1. A Venus lander, designed to sample the atmosphere and surface of Venus, would have to perform
science operations as components and subsystems degrade and fail;
2. A Trojan asteroid tour spacecraft would spend significant time cruising to its ultimate destination
(essentially hibernating to save on operations costs), then upon arrival, would have to act as its
own surveyor, finding new objects and targets of opportunity as it approaches each asteroid,
requiring response on short notice; and
3. A MSR campaign would not only be required to perform fast reconnaissance over long distances
on the surface of Mars, interact with an unknown physical surface, and handle degradations and
faults, but would also contain multiple components (launch vehicle, cruise stage, entry and
landing vehicle, surface rover, ascent vehicle, orbiting cache, and Earth return vehicle) that
dramatically increase the need for resilience to failure across the complex system.
The concept of resilience and its relevance and application in various domains was a focus during the
study, with several definitions of resilience proposed and discussed. While there was substantial variation
in the specifics, there was a common conceptual core that emergedâadaptation in the presence of
changing circumstances. These changes were couched in various waysâanomalies, disruptions,
discoveriesâbut they all ultimately had to do with changes in underlying assumptions. Invalid
assumptions, whether due to unexpected changes in the environment, or an inadequate understanding of
interactions within the system, may cause unexpected or unintended system behavior. A system is
resilient if it continues to perform the intended functions in the presence of invalid assumptions.
Our study focused on areas of resilience that we felt needed additional exploration and integration,
namely system and software architectures and capabilities, and autonomy technologies. (While also an
important consideration, resilience in hardware is being addressed in multiple other venues, including
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other KISS studies.) The study consisted of two workshops, separated by a seven-month focused study
period. The first workshop (Workshop #1) explored the âproblem spaceâ as an organizing theme, and the
second workshop (Workshop #2) explored the âsolution spaceâ. In each workshop, focused discussions
and exercises were interspersed with presentations from participants and invited speakers.
The study period between the two workshops was organized as part of the synthesis activity during the
first workshop. The study participants, after spending the initial days of the first workshop discussing the
nature of resilience and its impact on future science missions, decided to split into three focus groups,
each with a particular thrust, to explore specific ideas further and develop material needed for the second
workshop. The three focus groups and areas of exploration were:
1. Reference missions: address/refine the resilience needs by exploring a set of reference missions
2. Capability survey: collect, document, and assess current efforts to develop capabilities and
technology that could be used to address the documented needs, both inside and outside NASA
3. Architecture: analyze the impact of architecture on system resilience, and provide principles and
guidance for architecting greater resilience in our future systems
The key product of the second workshop was a set of capability roadmaps pertaining to the three
reference missions selected for their representative coverage of the types of space missions envisioned for
the future. From these three roadmaps, we have extracted several common capability patterns that would
be appropriate targets for near-term technical development: one focused on graceful degradation of
system functionality, a second focused on data understanding for science and engineering applications,
and a third focused on hazard avoidance and environmental uncertainty. Continuing work is extending
these roadmaps to identify candidate enablers of the capabilities from the following three categories:
architecture solutions, technology solutions, and process solutions.
The KISS study allowed a collection of diverse and engaged engineers, researchers, and scientists to think
deeply about the theory, approaches, and technical issues involved in developing and applying resilience
capabilities. The conclusions summarize the varied and disparate discussions that occurred during the
study, and include new insights about the nature of the challenge and potential solutions:
1. There is a clear and definitive need for more resilient space systems. During our study period,
the key scientists/engineers we engaged to understand potential future missions confirmed the
scientific and risk reduction value of greater resilience in the systems used to perform these
missions.
2. Resilience can be quantified in measurable termsâproject cost, mission risk, and quality of
science return. In order to consider resilience properly in the set of engineering trades performed
during the design, integration, and operation of space systems, the benefits and costs of resilience
need to be quantified. We believe, based on the work done during the study, that appropriate
metrics to measure resilience must relate to risk, cost, and science quality/opportunity. Additional
work is required to explicitly tie design decisions to these first-order concerns.
3. There are many existing basic technologies that can be applied to engineering resilient space
systems. Through the discussions during the study, we found many varied approaches and
research that address the various facets of resilience, some within NASA, and many more
beyond. Examples from civil architecture, Department of Defense (DoD) / Defense Advanced
Research Projects Agency (DARPA) initiatives, âsmartâ power grid control, cyber-physical
systems, software architecture, and application of formal verification methods for software were
identified and discussed. The variety and scope of related efforts is encouraging and presents
many opportunities for collaboration and development, and we expect many collaborative
proposals and joint research as a result of the study.
4. Use of principled architectural approaches is key to managing complexity and integrating
disparate technologies. The main challenge inherent in considering highly resilient space
systems is that the increase in capability can result in an increase in complexity with all of the
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risks and costs associated with more complex systems. What is needed is a better way of
conceiving space systems that enables incorporation of capabilities without increasing
complexity. We believe principled architecting approaches provide the needed means to convey a
unified understanding of the system to primary stakeholders, thereby controlling complexity in
the conception and development of resilient systems, and enabling the integration of disparate
approaches and technologies. A representative architectural example is included in Appendix F.
5. Developing trusted resilience capabilities will require a diverse yet strategically directed
research program. Despite the interest in, and benefits of, deploying resilience space systems, to
date, there has been a notable lack of meaningful demonstrated progress in systems capable of
working in hazardous uncertain situations. The roadmaps completed during the study, and
documented in this report, provide the basis for a real funded plan that considers the required
fundamental work and evolution of needed capabilities.
Exploring space is a challenging and difficult endeavor. Future space missions will require more
resilience in order to perform the desired science in new environments under constraints of development
and operations cost, acceptable risk, and communications delays. Development of space systems with
resilient capabilities has the potential to expand the limits of possibility, revolutionizing space science by
enabling as yet unforeseen missions and breakthrough science observations.
Our KISS study provided an essential venue for the consideration of these challenges and goals.
Additional work and future steps are needed to realize the potential of resilient systemsâthis study
provided the necessary catalyst to begin this process
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
Disturbance Detection, Identification, and Recovery by Gait Transition in Legged Robots
We present a framework for detecting, identifying, and recovering within stride from faults and other leg contact disturbances encountered by a walking hexapedal robot. Detection is achieved by means of a software contactevent sensor with no additional sensing hardware beyond the commercial actuatorsâ standard shaft encoders. A simple finite state machine identifies disturbances as due either to an expected ground contact, a missing ground contact indicating leg fault, or an unexpected âwallâ contact. Recovery proceeds as necessary by means of a recently developed topological gait transition coordinator. We demonstrate the efficacy of this system by presenting preliminary data arising from two reactive behaviors â wall avoidance and leg-break recovery. We believe that extensions of this framework will enable reactive behaviors allowing the robot to function with guarded autonomy under widely varying terrain and self-health conditions
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