Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Accountability (1)
- Agent-based models (1)
- Algorithm (1)
- Artificial intelligence (1)
- ChatGPT (1)
-
- Chatbots (1)
- Communication (1)
- Community (1)
- GPM (1)
- GSO (1)
- Hand-held robots (1)
- Human-robot collaboration (1)
- Hypothesis testing (1)
- Laparoscopy (1)
- Large language models (1)
- Minimally invasive surgery (1)
- Narrative generation (1)
- Narratives (1)
- Natural language generation (1)
- Natural language processing (1)
- Prompt design (1)
- Prompt engineering (1)
- Scaling multi-robot systems (1)
- Simulation (1)
- Social norms (1)
- Spillage-free specimen retrieval (1)
- Structured prompt (1)
- Surgical robotics (1)
- Swarm (1)
- Unknown environment (1)
- Publication Type
Articles 1 - 3 of 3
Full-Text Articles in Engineering
Data-Driven Predictive Modeling To Enhance Search Efficiency Of Glowworm-Inspired Robotic Swarms In Multiple Emission Source Localization Tasks, Payal Nandi
Mechanical & Aerospace Engineering Theses & Dissertations
In time-sensitive search and rescue applications, a team of multiple mobile robots broadens the scope of operational capabilities. Scaling multi-robot systems (< 10 agents) to larger robot teams (10 – 100 agents) using centralized coordination schemes becomes computationally intractable during runtime. One solution to this problem is inspired by swarm intelligence principles found in nature, offering the benefits of decentralized control, fault tolerance to individual failures, and self-organizing adaptability. Glowworm swarm optimization (GSO) is unique among swarm-based algorithms as it simultaneously focuses on searching for multiple targets. This thesis presents GPR-GSO—a modification to the GSO algorithm that incorporates Gaussian Process Regression (GPR) based data-driven predictive modeling—to improve the search efficiency of robotic swarms in multiple emission source localization tasks. The problem formulation and methods are presented, followed by numerical simulations to illustrate the working of the algorithm. Results from a comparative analysis show that the GPR-GSO algorithm exceeds the performance of the benchmark GSO algorithm on evaluation metrics of swarm size, search completion time, and travel distance.
Roboretrieve--In A Dual Role As A Hand-Held Surgical Robot And A Collaborative Robot End-Effector To Perform Spillage-Free Specimen Retrieval In Laparoscopy, Siqin Dong
Mechanical & Aerospace Engineering Theses & Dissertations
Recent advances in surgical robotics attempt to overcome limitations of manual surgery by augmenting the surgeon’s capabilities while performing suturing, incision, retraction, and retrieval tasks. This dissertation presents novel approaches for spillage-free specimen retrieval in confined spaces, targeted toward the surgical domain of minimally invasive robotic surgery. The retrieval task involves extraction of a resected specimen, residing in the abdominal cavity, completely outside of the patient’s body. A major challenge in this context is the spillage of content being retrieved, which may cause dissemination of malignancy. To address this challenge, this dissertation develops RoboRetrieve, a portable hand-held robot that …
A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore
A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore
VMASC Publications
Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …