Collaborative Research: SHF: Small: Interactive Synthesis and Repair For Robot Programs

合作研究：SHF：小型：机器人程序的交互式合成和修复

• 批准号: 2006404
• 负责人: Joydeep Biswas
• 金额: $ 25万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006404&HistoricalAwards=false
• 关键词: Collaborative; Research; SHF; Small; Interactive

Over the past few years, robots have started to be deployed in unstructured human environments. There are hundreds of robots deployed in hospitals, hotels, and supermarkets. Unfortunately, the software that runs on robots is programmed using low-level abstractions and languages, and is hard to transfer across robots and environments. In addition robotic software requires complex control logic to ensure that robots are safe and well-behaved in all situations. Thus, robot software is extraordinarily hard to write and maintain. This research project develops tools and techniques to make robot software safer, easier to write, and easier to maintain. The intellectual merits of the project are the development of (1) techniques for fixing bugs in robot software, based on advances to automatic program repair and program synthesis; (2) abstractions for writing robot software that can automatically handle certain kinds of failures, based on new programming-language design; (3) methods for checking the correctness of robot software, based on new program-verification techniques. The project's broader significance and importance are that it helps make robot software easier to write and maintain, and cheaper, safer, and more reliable. The project encourages further research at the intersection of programming languages and robotics by publishing research results and releasing open-source software. The project also involves high-school outreach workshops to broaden participation in computing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在过去的几年里，机器人已经开始部署在非结构化的人类环境中。医院、酒店和超市部署了数百台机器人。不幸的是，在机器人上运行的软件是使用低级抽象和语言进行编程的，并且很难在机器人和环境之间传输。此外，机器人软件需要复杂的控制逻辑，以确保机器人在所有情况下都安全且表现良好。因此，机器人软件非常难以编写和维护。该研究项目开发工具和技术，使机器人软件更安全、更易于编写和维护。该项目的智力优点是开发（1）基于自动程序修复和程序合成的进步来修复机器人软件中的错误的技术； （2）基于新的编程语言设计，编写能够自动处理某些类型故障的机器人软件的抽象； (3)基于新的程序验证技术的机器人软件正确性检查方法。该项目更广泛的意义和重要性在于，它有助于使机器人软件更易于编写和维护，并且更便宜、更安全、更可靠。该项目通过发布研究成果和发布开源软件来鼓励编程语言和机器人技术交叉领域的进一步研究。该项目还涉及高中外展研讨会，以扩大对计算的参与。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Iterative Program Synthesis for Adaptable Social Navigation

适应性社交导航的迭代程序综合

• 发表时间: 2021
• 期刊: IEEE/RSJ International Conference on
• 作者: Holtz, Jarrett;Andrews, Simon;Guha, Arjun;Biswas, Joydeep
• 通讯作者: Biswas, Joydeep

SocialGym: A Framework for Benchmarking Social Robot Navigation

• DOI: 10.1109/iros47612.2022.9982021
• 发表时间: 2021-09
• 期刊: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 作者: Jarrett Holtz;Joydeep Biswas

IV-SLAM: Introspective Vision for Simultaneous Localization and Mapping

• 发表时间: 2020-08
• 期刊: ArXiv
• 作者: Sadegh Rabiee;Joydeep Biswas

Robot Action Selection Learning via Layered Dimension Informed Program Synthesis

• 发表时间: 2020-08
• 作者: Jarrett Holtz;Arjun Guha;Joydeep Biswas