Collaborating Authors

Planning & Scheduling

Transforming advanced manufacturing through Industry 4.0


The last decade has seen companies operating under increasing levels of disruption. Quickly changing customer preferences, as well as demand uncertainty and disruptions, are challenging planning systems to unprecedented degrees. National security interests, trade barriers, and logistics disruptions are pushing businesses to find alternatives to globalized supply chains. Major swings in demand are calling for drastic operational and capital cost reduction in some areas and rapid growth in others. Physical distancing and remote work are forcing manufacturers to reconfigure manufacturing flows and management.

Humans in the loop help robots find their way: Computer scientists' interactive program aids motion planning for environments with obstacles


Engineers at Rice University have developed a method that allows humans to help robots "see" their environments and carry out tasks. The strategy called Bayesian Learning IN the Dark -- BLIND, for short -- is a novel solution to the long-standing problem of motion planning for robots that work in environments where not everything is clearly visible all the time. The peer-reviewed study led by computer scientists Lydia Kavraki and Vaibhav Unhelkar and co-lead authors Carlos Quintero-Peña and Constantinos Chamzas of Rice's George R. Brown School of Engineering was presented at the Institute of Electrical and Electronics Engineers' International Conference on Robotics and Automation in late May. The algorithm developed primarily by Quintero-Peña and Chamzas, both graduate students working with Kavraki, keeps a human in the loop to "augment robot perception and, importantly, prevent the execution of unsafe motion," according to the study. To do so, they combined Bayesian inverse reinforcement learning (by which a system learns from continually updated information and experience) with established motion planning techniques to assist robots that have "high degrees of freedom" -- that is, a lot of moving parts.

Global Big Data Conference


Managing a complex workforce has never been an easy task, and the pandemic only made it that much worse. Not only have processes surrounding hiring, firing, payroll and benefits become more difficult, but the work-from-home and rising freelance culture is adding new stresses to HR – all at a time when the pace of business is increasing rapidly and driving a greater need for workforce flexibility. Necessity is the mother of innovation, however, and in this case organizations are turning to artificial intelligence (AI) to not only lighten the load on traditional human resource management systems, but to engage the workforce in novel new ways. Far from putting humans out of work, these tools are helping people work better and improve their work-life balance. Tech blogger Srikanth claims AI is transforming workforce management in three crucial ways.

PGA Tour steps up response to rival LIV Golf league with proposed schedule changes, purse increases: reports

FOX News

Fox News Flash top headlines are here. Check out what's clicking on The PGA Tour has stepped up its response to the rival Saudi-backed golf league this week, proposing an eight-event series worth at least $160 million in total prize earnings, according to multiple reports. Commissioner Jay Monahan met with players on Tuesday ahead of this week's Travelers Championship to discuss changes to the tour schedule that will include "eight limited-field no-cut events, with purses of $20 million or more each, for the top 50 finishers in the prior season's FedEx Cup standings," Gold Digest reported, citing several players present at the meeting. PGA Tour Commissioner Jay Monahan speaks to the media during a press conference prior to The Players Championship on the Stadium Course at TPC Sawgrass on March 8, 2022 in Ponte Vedra Beach, Florida.

Planning with Critical Section Macros: Theory and Practice

Journal of Artificial Intelligence Research

Macro-operators (macros) are a well-known technique for enhancing performance of planning engines by providing "short-cuts" in the state space. Existing macro learning systems usually generate macros by considering most frequent action sequences in training plans. Unfortunately, frequent action sequences might not capture meaningful activities as a whole, leading to a limited beneficial impact for the planning process. In this paper, inspired by resource locking in critical sections in parallel computing, we propose a technique that generates macros able to capture whole activities in which limited resources (e.g., a robotic hand, or a truck) are used. Specifically, such a Critical Section macro starts by locking the resource (e.g., grabbing an object), continues by using the resource (e.g., manipulating the object) and finishes by releasing the resource (e.g., dropping the object). Hence, such a macro bridges states in which the resource is locked and cannot be used. We also introduce versions of Critical Section macros dealing with multiple resources and phased locks. Usefulness of macros is evaluated using a range of state-of-the-art planners, and a large number of benchmarks from the deterministic and learning tracks of recent editions of the International Planning Competition.

Ambulatory surgery center's virtual care platform helps boost productivity and patient satisfaction


The Surgical Center at Columbia Orthopaedic Group in Missouri, like so many ambulatory surgery centers across the country, does procedures today that are far more complex than those it did five years ago. "In the past, we haven't worried as much about coordinating care across the patient journey, from preoperative education to surgical aftercare," said Andrew Lovewell, administrator. "But as the sheer complexity of our procedures increased, we wanted our patients to have remote access to instructional videos and better connectivity with their care teams. "We didn't want to complete surgeries in a transactional way, without any intimacy or continued communication with the patient to ensure they were experiencing excellent results," he added. As one of the top surgery centers in the nation per Newsweek for both 2021 and 2022, The Surgical Center at Columbia Orthopaedic Group felt it was representative of its quality and reputation to create a system that improved the care it offered patients. "During the early stages of the pandemic, we had many patients that were afraid of going to physical therapy, and several facilities were shut down for extended periods," Lovewell recalled. "We knew we needed to create an environment of safety while still retaining control over our patients' recovery journey.

Core Challenges in Embodied Vision-Language Planning

Journal of Artificial Intelligence Research

Recent advances in the areas of multimodal machine learning and artificial intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Embodied AI. Whereas many approaches and previous survey pursuits have characterised one or two of these dimensions, there has not been a holistic analysis at the center of all three. Moreover, even when combinations of these topics are considered, more focus is placed on describing, e.g., current architectural methods, as opposed to also illustrating high-level challenges and opportunities for the field. In this survey paper, we discuss Embodied Vision-Language Planning (EVLP) tasks, a family of prominent embodied navigation and manipulation problems that jointly use computer vision and natural language. We propose a taxonomy to unify these tasks and provide an in-depth analysis and comparison of the new and current algorithmic approaches, metrics, simulated environments, as well as the datasets used for EVLP tasks. Finally, we present the core challenges that we believe new EVLP works should seek to address, and we advocate for task construction that enables model generalizability and furthers real-world deployment.

All You Need to Know About Industrial Automation and Robotics - The AI Journal


The use of computers and control systems in every industry has become very important in the last two decades. This is because computers are the backbone of the development of an industry. Information technology (computers, control systems) is used to handle all types of industrial methods; it also controls the processes of the planted machinery, increases efficiency, manually replaces the industry's workers, and enhances the speed and quality of that industry. All of these uses are called Industrial automation and robotics. Industrial automation and robotics cover a wide range of control systems from any production methods assembly lines, medical and aircraft etc.

The Application of AI Technology in GPU Scheduling Algorithm Optimization


The Application of AI Technology in GPU Scheduling Algorithm Optimization | Zhancai Yan, Yaqiu Liu, Hongrun Shao | Artificial intelligence, Computer science, CUDA, GPU cluster, nVidia, Task scheduling

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