Scalable Robotic Intra-Logistics with Answer Set Programming

Over time, Answer Set Programming (ASP) has gained traction as a versatile logic programming semantics with performant processing systems, used by a growing number of significant applications in academia and industry. However, this development is threatened by a lack of commonly accepted design patterns and techniques for ASP to address dynamic application on a real-world scale. To this end, we identified robotic intra-logistics as representative scenario, a major domain of interest in the context of the fourth industrial revolution. For this setting, we aim to provide a scalable and efficient ASP-based solutions by (1) stipulating a standardized test and benchmark framework; (2) leveraging existing ASP techniques through new design patterns; and (3) extending ASP with new functionalities. In this paper we will expand on the subject matter as well as detail our current progress and future plans

Multi-Shot Stream Reasoning in Answer Set Programming: A Preliminary Report

In the past, we presented a first approach for stream reasoning using Answer Set Programming (ASP). At the time, we implemented an exhaustive wrapper for our underlying ASP system, clingo, to enable reasoning over continuous data streams. Nowadays, clingo natively supports multi-shot solving: a technique for processing continuously changing logic programs. In the context of stream reasoning, this allows us to directly implement seamless sliding-window-based reasoning over emerging data. In this paper, we hence present an exhaustive update to our stream reasoning approach that leverages multi-shot solving. We describe the implementation of the stream reasoner's architecture, and illustrate its workflow via job shop scheduling as a running example

Logic programming for deliberative robotic task planning

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured plan to satisfy a prescribed goal, given specifications on the robot and the environment. In this manuscript, we present a survey on recent advances in the application of logic programming to the problem of task planning. Logic programming offers several advantages compared to other approaches, including greater expressivity and interpretability which may aid in the development of safe and reliable robots. We analyze different planners and their suitability for specific robotic applications, based on expressivity in domain representation, computational efficiency and software implementation. In this way, we support the robotic designer in choosing the best tool for his application

AN ANALYSIS OF HOW THE U.S. GOVERNMENT CAN EFFECTIVELY TACKLE SUPPLY CHAIN BARRIERS TO SCALE UP THE LOW COST UNMANNED AERIAL VEHICLE (UAV) SWARMING TECHNOLOGY (LOCUST) PROGRAM

The LOCUST program is a scalable system of inexpensive swarming unmanned aerial vehicles to provide disruptive capability in contested environments against anti-area access denial defenses, enabling manned strike operations and localized landing site superiority with reduced cost, risk, and operator launch and workload. Our research and analysis will emphasize the challenges of moving from a U.S. Special Operations Command (USSOCOM) effort to a large program of record. Specific supply chain concerns that will be addressed include: 1) DOD organizational structure; 2) service-specific objectives and currently operating platforms; 3) requirements generation and related procurements to include production and quality challenges; 4) safety and quality assurance standards; 5) lead times, inventory plans, and throughput to include supplier base considerations and consolidations; and 6) latest evolving technologies and continuous improvement principles. Our team will utilize the Define, Measure, Analyze, Improve, Control (DMAIC) evaluative methodology that focuses on data-driven improvement cycles to better optimize process, design and results. Our results and recommendations highlighted multiple strategies that the Office of Naval Research (ONR) must focus on when developing the LOCUST supply chain. These conclusions and findings address both current supply chain development opportunities for the LOCUST program, as well as where the program must focus its efforts in the future.http://archive.org/details/ananalysisofhowt1094563516Civilian, Department of the NavyCivilian, Department of the ArmyCivilian, Department of the ArmyApproved for public release; distribution is unlimited