[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84806-en":3,"doc-seo-84806-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84806,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",6,"Technology","Socially Aware Autonomous Doorway Traversal and Payload Delivery for Emergency Assistance","This work addresses robot-assisted emergency evacuation by combining two key capabilities: opening ADA-compliant doors ahead of evacuees to keep exits clear, and retrieving rescue equipment and delivering it to on-site responders. The approach integrates multi-task reasoning in real time, requiring door-button and equipment localization plus continuous awareness of nearby people to avoid obstructing evacuation. A behavior-tree framework selects high-level tasks via environmental triggers, adapting as scenarios change. Evaluations on a Toyota Human Support Robot report 97 successes across 105 trials.","Socially-Aware Autonomous Doorway Traversaland Payload Delivery for Emergency Assistance  \nAndrew Snowdy, Ananya Trivedi, Sarvesh Prajapati, Lorena Maria Genua, and Tas¸kın Padır1  \narXiv :2607 .053 15v2 [ cs .RO] 7 Jul 2026  \nAbstract—In this work, we focus on the scenario of a robotassisted emergency evacuation. We consider two capabilities relevant to such a setting. The first is opening doors ahead of the people being evacuated, so that their path toward an exit stays clear. The second is retrieving rescue equipment and delivering it to the emergency responders carrying out the evacuation. From a systems perspective, this involves several tasks at once. The robot must locate ADA-compliant door buttonsand the rescue equipment it needs to retrieve. Additionally, it must remain aware of the people around it and adapt its behavior to them, so that it supports the evacuation rather than getting in the way. We address these demands with a behavior tree at the core of our framework. This structure is chosen for its ability to select high-level tasks based on environmental triggers, and to extend to new situations as they arise. We evaluate the system in 105 trials on the Toyota Human Support Robot, across four hardware and three simulation scenarios. These trials capture the decisions the robot must make in this setting: whether to press a door button, yield to a nearby person, walk through a door someone else is holding, or first retrieve rescue equipment before traversing the door. Overall, the system completes 97 of the 105 trials successfully. These results suggest our framework provides a practical basis for robotic assistance in broader emergency response tasks. Code and video demonstrations are available at [https://github.com/AndrewSnowdy/hsr](https://github.com/AndrewSnowdy/hsr mm control)[ ](https://github.com/AndrewSnowdy/hsr mm control)[mm](https://github.com/AndrewSnowdy/hsr mm control)[ ](https://github.com/AndrewSnowdy/hsr mm control)[control](https://github.com/AndrewSnowdy/hsr mm control).  \nI. INTRODUCTION  \nThe July 2025 Gabriel House fire in Fall River, Massachusetts [1] claimed the lives of ten residents of an assisted living facility. Many of the victims had limited mobility and were unable to move through narrow hallways once the primary elevator failed. In high-stress events like this, infrastructure such as ADA-compliant doors can turn into bottlenecks. They are slow to open, may require a button press, and can force a queue to form as people wait to pass through one at a time. Evacuating people safely under these conditions is difficult, highlighting a clear need for systems that can assist an evacuation as it unfolds.  \nThe authors are with the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA. Emails: {snowdy.a, trivedi.ana, prajapati.s, genua.l, [t.padir](t.padir}@northeastern.edu)[}](t.padir}@northeastern.edu)[@northeastern.edu](t.padir}@northeastern.edu)  \n1Tas¸kın Padır holds concurrent appointments as a Professor of Electrical and Computer Engineering at Northeastern University and as an Amazon Scholar. This paper describes work performed at Northeastern University and is not associated with Amazon.  \nThis research was funded, in part, by the Advanced Research Projects Agency for Health (ARPA-H) Agreement No. 140D042590012 . The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.  \nFig. 1. Toyota Human Support Robot (HSR) used in our experiments. The two-fingered gripper grasps payloads such as water bottles and flashlightsand presses the ADA-compliant door button, while the omnidirectional wheelbase provides planar mobility.  \nIn this work, we investigate how indoor service robots can help with tasks like these. Our focus is on clearing pathways for people as a rescue unfolds. If a robot can keep doorways op","cbCainC631Qynw2L","https://ap.wps.com/l/cbCainC631Qynw2L","pdf",4115767,1,8,"English","en",105,"# Introduction\n## Emergency evacuation bottlenecks\n## Core capabilities and motivation\n## System design overview\n## Behavior-tree framework","[{\"question\":\"What two main capabilities does the robot provide in emergency evacuation?\",\"answer\":\"The robot opens ADA-compliant doors ahead of evacuees and retrieves rescue equipment to deliver it to emergency responders.\"},{\"question\":\"Why is doorway traversal challenging during evacuations?\",\"answer\":\"ADA-compliant doors can be slow to open, may require button presses, and can force people to form queues, especially when infrastructure like elevators fails.\"},{\"question\":\"How does the proposed framework decide what the robot should do during trials?\",\"answer\":\"It uses a behavior tree that selects high-level tasks based on environmental triggers and people intent, such as pressing a door button, yielding, walking through a held door, or retrieving equipment 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