Lifelong Multi-Agent Path Finding in Large-Scale Warehouses

Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where agents are constantly engaged with new goal locations, such as in large-scale automated warehouses. We propose a new framework Rolling-Horizon Collision Resolution (RHCR) for solving lifelong MAPF by decomposing the problem into a sequence of Windowed MAPF instances, where a Windowed MAPF solver resolves collisions among the paths of the agents only within a bounded time horizon and ignores collisions beyond it. RHCR is particularly well suited to generating pliable plans that adapt to continually arriving new goal locations. We empirically evaluate RHCR with a variety of MAPF solvers and show that it can produce high-quality solutions for up to 1,000 agents (= 38.9\% of the empty cells on the map) for simulated warehouse instances, significantly outperforming existing work.Comment: Published at AAAI 202

A decentralized scheduling algorithm for time synchronized channel hopping

Abstract. Time Synchronized Channel Hopping (TSCH) is an existing medium access control scheme which enables robust communication through channel hopping and high data rates through synchronization. It is based on a time-slotted architecture, and its correct functioning depends on a schedule which is typically computed by a central node. This paper presents, to our knowledge, the first scheduling algorithm for TSCH networks which both is distributed and which copes with a mobile nodes. Two scheduling algorithms are presented. Aloha-based scheduling allocates one frequency channel for broadcasting advertisements for new neighbors. Reservation-based scheduling augments Aloha-based scheduling with a dedicated slot for targeted advertisements based on gossip information. A mobile ad-hoc network with frequent connectivity changes is simulated, and the performance of the two proposed algorithms is assessed against the optimal case. Reservation-based scheduling performs significantly better than Aloha-based scheduling, suggesting that the improved network reactivity is worth the increased algorithmic complexity and resource consumption

Viability-based computation of spatially constrained minimum time trajectories for an autonomous underwater vehicle: implementation and experiments.

A viability algorithm is developed to compute the constrained minimum time function for general dynamical systems. The algorithm is instantiated for a specific dynamics(Dubin’s vehicle forced by a flow field) in order to numerically solve the minimum time problem. With the specific dynamics considered, the framework of hybrid systems enables us to solve the problem efficiently. The algorithm is implemented in C using epigraphical techniques to reduce the dimension of the problem. The feasibility of this optimal trajectory algorithm is tested in an experiment with a Light Autonomous Underwater Vehicle (LAUV) system. The hydrodynamics of the LAUV are analyzed in order to develop a low-dimension vehicle model. Deployment results from experiments performed in the Sacramento River in California are presented, which show good performance of the algorithm.trajectories; underwater vehicle; viability algorithm; hybrid systems; implementation;

Autonomous Searching and Tracking of a River using an UAV

Abstract—Surveillance operations include inspecting and monitoring river boundaries, bridges and coastlines. An au-tonomous Unmanned Aerial Vehicle (UAV) can decrease the operational costs, expedite the monitoring process and be used in situations where a manned inspection is not possible. This paper addresses the problem of searching and mapping such littoral boundaries using an autonomous UAV based on visual feedback. Specifically, this paper describes an exploration system that equips a fixed wing UAV to autonomously search a given area for a specified structure (could be a river, a coastal line etc.), identify the structure if present and map the coordinates of the structure based on the images from the onboard sensor(could be vision or near infra-red). Experimental results with a fixed wing UAV searching and mapping the coordinates of a 2 mile stretch of a river with a cross track error of around 9 meters are presented. I

Antidepressants and youth suicide in New York City, 1999-2002

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41247/1/leon_antidepressants and youth suicide_2006.pd

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Actuated Mobile Sensing in Distributed, Unstructured Environments

Mobile sensor networks present opportunities for improved in situ sensing in complex hydrodynamic environments such as estuarial deltas. This dissertation considers the design and implementation of the mobile sensor network system that was built as part of the Floating Sensor Network project for use in the Sacramento-San Joaquin Delta in California over the 2007-2012 time period. Individual Lagrangian sensor units collect hydrodynamic state information, which is then transmitted to a centralized server and assimilated to produce a state estimate for the entire hydrodynamic system. Physical obstacles, including the shoreline and natural vegetation, present a major challenge to operating mobile sensors in estuarial environments. Actuated mobile sensors are shown to be a viable solution; appropriate control techniques allow these sensors to avoid obstacles, meet navigational goals, and still collect the Lagrangian data necessary for the sensing objective. Issues addressed include physical design, communication techniques for mobile sensor networks, control schemes for fleets of underactuated vehicles in unstructured flow environments, assimilation techniques for mobile Lagrangian data, and field experiments to validate and demonstrate the actuated mobile Lagrangian sensor concept

Actuated Mobile Sensing in Distributed, Unstructured Environments

Mobile sensor networks present opportunities for improved in situ sensing in complex hydrodynamic environments such as estuarial deltas. This dissertation considers the design and implementation of the mobile sensor network system that was built as part of the Floating Sensor Network project for use in the Sacramento-San Joaquin Delta in California over the 2007-2012 time period. Individual Lagrangian sensor units collect hydrodynamic state information, which is then transmitted to a centralized server and assimilated to produce a state estimate for the entire hydrodynamic system. Physical obstacles, including the shoreline and natural vegetation, present a major challenge to operating mobile sensors in estuarial environments. Actuated mobile sensors are shown to be a viable solution; appropriate control techniques allow these sensors to avoid obstacles, meet navigational goals, and still collect the Lagrangian data necessary for the sensing objective. Issues addressed include physical design, communication techniques for mobile sensor networks, control schemes for fleets of underactuated vehicles in unstructured flow environments, assimilation techniques for mobile Lagrangian data, and field experiments to validate and demonstrate the actuated mobile Lagrangian sensor concept