| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
|
| Initial Amendment Date: | July 27, 2017 |
| Latest Amendment Date: | July 27, 2017 |
| Award Number: | 1724070 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Jie Yang
jyang@nsf.gov (703)292-4768 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2017 |
| End Date: | August 31, 2021 (Estimated) |
| Total Intended Award Amount: | $459,470.00 |
| Total Awarded Amount to Date: | $459,470.00 |
| Funds Obligated to Date: |
|
| History of Investigator: |
|
| Recipient Sponsored Research Office: |
940 GRACE HALL NOTRE DAME IN US 46556-5708 (574)631-7432 |
| Sponsor Congressional District: |
|
| Primary Place of Performance: |
Fitzpatrick Hall Notre Dame IN US 46556-5637 |
| Primary Place of
Performance Congressional District: |
|
| Unique Entity Identifier (UEI): |
|
| Parent UEI: |
|
| NSF Program(s): | S&AS - Smart & Autonomous Syst |
| Primary Program Source: |
|
| Program Reference Code(s): |
|
| Program Element Code(s): |
|
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Future space missions will increasingly rely on autonomous robots like the NASA Valkyrie human-centered robot for deploying equipment, assisting astronauts, and maintaining facilities in real world partially-observable and cluttered environments. Despite significant progress in robotic mobility, manipulation, and perception, there has been relatively little progress on providing formal performance guarantees for these integrated systems. Formal guarantees are critical for achieving long term autonomy, particularly for robots performing complex tasks requiring successful execution of multiple component subtasks. Thus, the goal of this project is to develop performance guarantees for space robots operating in unstructured real world environments. Although robots are used as design examples, the project is of a basic research nature and the results can have impacts on other fields, such as sensor/actuator networks, manufacturing and transportation systems. The multidisciplinary approach taken for this project will help broaden participation of underrepresented groups and positively impact engineering and computer science education.
The objective of this project is to develop new methods to synthesize coordinated manipulation and locomotion plans and control policies that verifiably adhere to formal mission specifications. There are two major thrusts. First, the PIs plan to develop manipulation, locomotion, and motion primitives that can provide performance guarantees in unstructured, partially observable, and dynamic environments. The focus will be on using methods from perception and planning under uncertainty to provide guarantees in cluttered and partially observable environments. The PIs will also leverage new tools from hybrid systems and sampling based methods to achieve controllers with verifiable guarantees through contact mode switches. Second, the PIs plan to devise methods to automatically synthesize mission plans in a way that can guarantee the accomplishment of high-level mission goals or bound the probability of failure. The focus will be on automatic and learning-based design, enabling the system to adapt to changing environments, uncertain faults and potential adversaries. Most of the work performed under this project will be demonstrated in the context of complex space tasks inspired by NASA scenarios.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Intelligent Physical Systems (IPS) can perceive, reason about, and act upon their environment. The overall goal of the project is to study and devise algorithms and embodiments for humanoid locomotion and manipulation control, behavior learning and composition, verification, and synthesis that fulfill formal mission specifications and to test these methods in real humanoid platforms emulating space mission setups. More concretely the project comprises scalable formal methods for design and control of high dimensional IPSs, centered around humanoid robots, that can achieve high-level missions for space setups in a verifiable manner in partially known, unstructured and dynamic physical environments. This is a collaborative project between UT Austin, University of Notre Dame, and Northeastern University.
The major research goal of Notre Dame team is to develop new formal methods and automatic synthesis of mission plans that can guarantee the accomplishment of high-level mission goals or bound the probability of failure. The key outcomes of the project by Notre Dame team include a set of formal methods to enable automatic synthesis of reactive mission plans that can guarantee the accomplishment of high-level mission goals in face of uncertainties. Although much progress has been made through controller synthesis from temporal logic specifications, existing approaches generally require conservative assumptions and do not scale well with system dimensionality. We therefore focused on the scalability issues of formal design and proposed a scalable, provably complete algorithm that synthesizes continuous trajectories for IPS to satisfy complex missions given as temporal logic specifications. To achieve scalability (with respect to the size of specifications and planning horizon), we harness highly efficient Boolean satisfiability (SAT) and Linear Programming (LP) solvers to find trajectories that satisfy non-convex Signal Temporal Logic (STL) specifications. The design methods were extended to hybrid systems with respect to temporal logic specifications, since many IPS exhbit hybrid dynamic nature. We further extend the formal design approach when IPS need to act with imperfect information about the environment by employing a counterexample-guided-inductive-synthesis approach for control from probabilistic signal temporal logic (PrSTL) specifications. The proposed design algorithms are proven sound and complete. Furthermore, the formal design methods are implemented as a Python toolbox. The results from this project could significantly advance the autonomy and systematic design of computational capabilities merging symbolic and sub-symbolic approaches for the next generation intelligent humanoid robotics systems performing high-level missions in a verifiable manner in space environments.
Last Modified: 12/30/2021
Modified by: Hai Lin
Please report errors in award information by writing to: awardsearch@nsf.gov.
