Ninad Jadhav, Sushmita Bhattacharya, Daniel Vogt, Yaniv Aluma, Pernille Tønnesen, Akarsh Prabhakara, Swarun Kumar, Shane Gero, Robert J Wood, Stephanie Gil
{"title":"Reinforcement learning-based framework for whale rendezvous via autonomous sensing robots.","authors":"Ninad Jadhav, Sushmita Bhattacharya, Daniel Vogt, Yaniv Aluma, Pernille Tønnesen, Akarsh Prabhakara, Swarun Kumar, Shane Gero, Robert J Wood, Stephanie Gil","doi":"10.1126/scirobotics.adn7299","DOIUrl":null,"url":null,"abstract":"<p><p>Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning-based routing (autonomy module) and synthetic aperture radar-based very high frequency (VHF) signal-based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an \"engineered whale\"-a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 95","pages":"eadn7299"},"PeriodicalIF":26.1000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Robotics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1126/scirobotics.adn7299","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning-based routing (autonomy module) and synthetic aperture radar-based very high frequency (VHF) signal-based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an "engineered whale"-a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists.
期刊介绍:
Science Robotics publishes original, peer-reviewed, science- or engineering-based research articles that advance the field of robotics. The journal also features editor-commissioned Reviews. An international team of academic editors holds Science Robotics articles to the same high-quality standard that is the hallmark of the Science family of journals.
Sub-topics include: actuators, advanced materials, artificial Intelligence, autonomous vehicles, bio-inspired design, exoskeletons, fabrication, field robotics, human-robot interaction, humanoids, industrial robotics, kinematics, machine learning, material science, medical technology, motion planning and control, micro- and nano-robotics, multi-robot control, sensors, service robotics, social and ethical issues, soft robotics, and space, planetary and undersea exploration.