Title: Autonomous Modification of Unstructured Environments with Found Material
The ability to autonomously modify their environment dramatically increases the capability of robots to operate in unstructured environments. We develop a specialized construction algorithm and robotic system that can autonomously build motion support structures with previously unseen objects. The approach is based on our prior work on adaptive ramp building algorithms, but it eliminates the assumption of having specialized building materials that simplify manipulation and planning for stability. Utilizing irregularly shaped stones makes the problem significantly more challenging since the outcome of individual placements is sensitive to details of contact geometry and friction, which are difficult to observe. To reuse the same high-level algorithm, we develop a new physics-based planner that explicitly considers the uncertainty produced by incomplete in-situ sensing and imprecision during pickup and placement. We demonstrate the approach on a robotic system that uses a newly developed gripper to reliably pick up stones with minimal additional sensors or complex grasp planning. The resulting system can build structures with more than 70 stones, which in turn provide traversable paths to previously inaccessible locations. more »« less
Liu, Y; Choi, J; Napp, N(
, Field and Service Robotics)
Ishigami, G; Yoshida, K
(Ed.)
The ability to build structures with autonomous robots using only found, minimally processed stones would be immensely useful, especially in remote areas. Assembly planning for dry-stacked structures, however, is difficult since both the state and action spaces are continuous, and stability is strongly affected by complex friction and contact constraints. We propose a planning algorithm for such assemblies that uses a physics simulator to find a small set of feasible poses and then evaluates them using a hierarchical filter. We carefully designed the heuristics for the filters to match our goal of building stable, free-standing walls. These plans are then executed open-loop with a robotic arm equipped with a wrist RGB-D camera. Experimental results show that the proposed planning algorithm can significantly improve the state of the art in robotic dry stacking.
Yahdi, Mohammed; Bracey, Zoe Buck(
, National Science Foundation - Hispanic-Serving Institutions (HSI) Program Principal Investigator (PI) Meeting, November 2019.)
Need/Motivation (e.g., goals, gaps in knowledge)
The ESTEEM implemented a STEM building capacity project through students’ early access to a sustainable and innovative STEM Stepping Stones, called Micro-Internships (MI). The goal is to reap key benefits of a full-length internship and undergraduate research experiences in an abbreviated format, including access, success, degree completion, transfer, and recruiting and retaining more Latinx and underrepresented students into the STEM workforce. The MIs are designed with the goals to provide opportunities for students at a community college and HSI, with authentic STEM research and applied learning experiences (ALE), support for appropriate STEM pathway/career, preparation and confidence to succeed in STEM and engage in summer long REUs, and with improved outcomes. The MI projects are accessible early to more students and build momentum to better overcome critical obstacles to success. The MIs are shorter, flexibly scheduled throughout the year, easily accessible, and participation in multiple MI is encouraged. ESTEEM also establishes a sustainable and collaborative model, working with partners from BSCS Science Education, for MI’s mentor, training, compliance, and building capacity, with shared values and practices to maximize the improvement of student outcomes.
New Knowledge (e.g., hypothesis, research questions)
Research indicates that REU/internship experiences can be particularly powerful for students from Latinx and underrepresented groups in STEM. However, those experiences are difficult to access for many HSI-community college students (85% of our students hold off-campus jobs), and lack of confidence is a barrier for a majority of our students. The gap between those who can and those who cannot is the “internship access gap.” This project is at a central California Community College (CCC) and HSI, the only affordable post-secondary option in a region serving a historically underrepresented population in STEM, including 75% Hispanic, and 87% have not completed college. MI is designed to reduce inequalities inherent in the internship paradigm by providing access to professional and research skills for those underserved students. The MI has been designed to reduce barriers by offering: shorter duration (25 contact hours); flexible timing (one week to once a week over many weeks); open access/large group; and proximal location (on-campus). MI mentors participate in week-long summer workshops and ongoing monthly community of practice with the goal of co-constructing a shared vision, engaging in conversations about pedagogy and learning, and sustaining the MI program going forward.
Approach (e.g., objectives/specific aims, research methodologies, and analysis)
Research Question and Methodology: We want to know: How does participation in a micro-internship affect students’ interest and confidence to pursue STEM? We used a mixed-methods design triangulating quantitative Likert-style survey data with interpretive coding of open-responses to reveal themes in students’ motivations, attitudes toward STEM, and confidence. Participants: The study sampled students enrolled either part-time or full-time at the community college. Although each MI was classified within STEM, they were open to any interested student in any major. Demographically, participants self-identified as 70% Hispanic/Latinx, 13% Mixed-Race, and 42 female. Instrument: Student surveys were developed from two previously validated instruments that examine the impact of the MI intervention on student interest in STEM careers and pursuing internships/REUs. Also, the pre- and post (every e months to assess longitudinal outcomes) -surveys included relevant open response prompts. The surveys collected students’ demographics; interest, confidence, and motivation in pursuing a career in STEM; perceived obstacles; and past experiences with internships and MIs. 171 students responded to the pre-survey at the time of submission.
Outcomes (e.g., preliminary findings, accomplishments to date)
Because we just finished year 1, we lack at this time longitudinal data to reveal if student confidence is maintained over time and whether or not students are more likely to (i) enroll in more internships, (ii) transfer to a four-year university, or (iii) shorten the time it takes for degree attainment. For short term outcomes, students significantly Increased their confidence to continue pursuing opportunities to develop within the STEM pipeline, including full-length internships, completing STEM degrees, and applying for jobs in STEM. For example, using a 2-tailed t-test we compared means before and after the MI experience. 15 out of 16 questions that showed improvement in scores were related to student confidence to pursue STEM or perceived enjoyment of a STEM career. Finding from the free-response questions, showed that the majority of students reported enrolling in the MI to gain knowledge and experience. After the MI, 66% of students reported having gained valuable knowledge and experience, and 35% of students spoke about gaining confidence and/or momentum to pursue STEM as a career.
Broader Impacts (e.g., the participation of underrepresented minorities in STEM; development of a diverse STEM workforce, enhanced infrastructure for research and education)
The ESTEEM project has the potential for a transformational impact on STEM undergraduate education’s access and success for underrepresented and Latinx community college students, as well as for STEM capacity building at Hartnell College, a CCC and HSI, for students, faculty, professionals, and processes that foster research in STEM and education. Through sharing and transfer abilities of the ESTEEM model to similar institutions, the project has the potential to change the way students are served at an early and critical stage of their higher education experience at CCC, where one in every five community college student in the nation attends a CCC, over 67% of CCC students identify themselves with ethnic backgrounds that are not White, and 40 to 50% of University of California and California State University graduates in STEM started at a CCC, thus making it a key leverage point for recruiting and retaining a more diverse STEM workforce.
Fletcher, Sarah; Zaniolo, Marta; Zhang, Mofan; Lickley, Megan(
, Proceedings of the National Academy of Sciences)
Climate oscillations ranging from years to decades drive precipitation variability in many river basins globally. As a result, many regions will require new water infrastructure investments to maintain reliable water supply. However, current adaptation approaches focus on long-term trends, preparing for average climate conditions at mid- or end-of-century. The impact of climate oscillations, which bring prolonged and variable but temporary dry periods, on water supply augmentation needs is unknown. Current approaches for theory development in nature-society systems are limited in their ability to realistically capture the impacts of climate oscillations on water supply. Here, we develop an approach to build middle-range theory on how common climate oscillations affect low-cost, reliable water supply augmentation strategies. We extract contrasting climate oscillation patterns across sub-Saharan Africa and study their impacts on a generic water supply system. Our approach integrates climate model projections, nonstationary signal processing, stochastic weather generation, and reinforcement learning–based advances in stochastic dynamic control. We find that longer climate oscillations often require greater water supply augmentation capacity but benefit more from dynamic approaches. Therefore, in settings with the adaptive capacity to revisit planning decisions frequently, longer climate oscillations do not require greater capacity. By building theory on the relationship between climate oscillations and least-cost reliable water supply augmentation, our findings can help planners target scarce resources and guide water technology and policy innovation. This approach can be used to support climate adaptation planning across large spatial scales in sectors impacted by climate variability.
Bui, Hoang-Dung; Nguyen, Son; Billah, U-H.; Le, Chuong; Tavakkoli, Alireza; La, Hung M.(
, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))
null
(Ed.)
Autonomous navigation of steel bridge inspection robots are essential for proper maintenance. Majority of existing robotic solutions for bridge inspection require human intervention to assist in the control and navigation. In this paper, a control system framework has been proposed for a previously designed ARA robot [1], which facilitates autonomous real-time navigation and minimizes human involvement. The mechanical design and control framework of ARA robot enables two different configurations, namely the mobile and inch-worm transformation. In addition, a switching control was developed with 3D point clouds of steel surfaces as the input which allows the robot to switch between mobile and inch-worm transformation. The surface availability algorithm (considers plane, area and height) of the switching control enables the robot to perform inch-worm jumps autonomously. The mobile transformation allows the robot to move on continuous steel surfaces and perform visual inspection of steel bridge structures. Practical experiments on actual steel bridge structures highlight the effective performance of ARA robot with the proposed control framework for autonomous navigation during visual inspection of steel bridges.
Fleming, Aaron; Stafford, Nicole; Huang, Stephanie; Hu, Xiaogang; Ferris, Daniel P; Huang, He(
, Journal of Neural Engineering)
Abstract Objective. Advanced robotic lower limb prostheses are mainly controlled autonomously. Although the existing control can assist cyclic movements during locomotion of amputee users, the function of these modern devices is still limited due to the lack of neuromuscular control (i.e. control based on human efferent neural signals from the central nervous system to peripheral muscles for movement production). Neuromuscular control signals can be recorded from muscles, called electromyographic (EMG) or myoelectric signals. In fact, using EMG signals for robotic lower limb prostheses control has been an emerging research topic in the field for the past decade to address novel prosthesis functionality and adaptability to different environments and task contexts. The objective of this paper is to review robotic lower limb Prosthesis control via EMG signals recorded from residual muscles in individuals with lower limb amputations. Approach. We performed a literature review on surgical techniques for enhanced EMG interfaces, EMG sensors, decoding algorithms, and control paradigms for robotic lower limb prostheses. Main results. This review highlights the promise of EMG control for enabling new functionalities in robotic lower limb prostheses, as well as the existing challenges, knowledge gaps, and opportunities on this research topic from human motor control and clinical practice perspectives. Significance. This review may guide the future collaborations among researchers in neuromechanics, neural engineering, assistive technologies, and amputee clinics in order to build and translate true bionic lower limbs to individuals with lower limb amputations for improved motor function.
Thangavelu, Vivek, da Silva, Maira Saboia, Choi, Jiwon, and Napp, Nils. Autonomous Modification of Unstructured Environments with Found Material. Retrieved from https://par.nsf.gov/biblio/10224842. 2020 IEEE International Conference on Robotics and Automation (ICRA) . Web. doi:10.1109/ICRA40945.2020.9197372.
Thangavelu, Vivek, da Silva, Maira Saboia, Choi, Jiwon, & Napp, Nils. Autonomous Modification of Unstructured Environments with Found Material. 2020 IEEE International Conference on Robotics and Automation (ICRA), (). Retrieved from https://par.nsf.gov/biblio/10224842. https://doi.org/10.1109/ICRA40945.2020.9197372
Thangavelu, Vivek, da Silva, Maira Saboia, Choi, Jiwon, and Napp, Nils.
"Autonomous Modification of Unstructured Environments with Found Material". 2020 IEEE International Conference on Robotics and Automation (ICRA) (). Country unknown/Code not available. https://doi.org/10.1109/ICRA40945.2020.9197372.https://par.nsf.gov/biblio/10224842.
@article{osti_10224842,
place = {Country unknown/Code not available},
title = {Autonomous Modification of Unstructured Environments with Found Material},
url = {https://par.nsf.gov/biblio/10224842},
DOI = {10.1109/ICRA40945.2020.9197372},
abstractNote = {The ability to autonomously modify their environment dramatically increases the capability of robots to operate in unstructured environments. We develop a specialized construction algorithm and robotic system that can autonomously build motion support structures with previously unseen objects. The approach is based on our prior work on adaptive ramp building algorithms, but it eliminates the assumption of having specialized building materials that simplify manipulation and planning for stability. Utilizing irregularly shaped stones makes the problem significantly more challenging since the outcome of individual placements is sensitive to details of contact geometry and friction, which are difficult to observe. To reuse the same high-level algorithm, we develop a new physics-based planner that explicitly considers the uncertainty produced by incomplete in-situ sensing and imprecision during pickup and placement. We demonstrate the approach on a robotic system that uses a newly developed gripper to reliably pick up stones with minimal additional sensors or complex grasp planning. The resulting system can build structures with more than 70 stones, which in turn provide traversable paths to previously inaccessible locations.},
journal = {2020 IEEE International Conference on Robotics and Automation (ICRA)},
author = {Thangavelu, Vivek and da Silva, Maira Saboia and Choi, Jiwon and Napp, Nils},
editor = {null}
}
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