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Update paper with replan, fix some author name stuff
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_bibliography/papers.bib

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@string{ral = {IEEE Robotics and Automation Letters}}
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@string{tro = {IEEE Transactions on Robotics}}
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@string{ijrr = {The International Journal of Robotics Research}}
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@misc{sabbadini2025replan,
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title = {Revisiting Replanning from Scratch: Real-Time Incremental Planning with Fast Almost-Surely Asymptotically Optimal Planners},
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author = {Mitchell E. C. Sabbadini and Andrew H. Liu and Joseph Ruan and Tyler S. Wilson and Zachary Kingston and Jonathan D. Gammell},
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abstract = {Robots operating in changing environments either predict obstacle changes and/or plan quickly enough to react to them. Predictive approaches require a strong prior about the position and motion of obstacles. Reactive approaches require no assumptions about their environment but must replan quickly and find high-quality paths to navigate effectively.
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Reactive approaches often reuse information between queries to reduce planning cost. These techniques are conceptually sound but updating dense planning graphs when information changes can be computationally prohibitive. It can also require significant effort to detect the changes in some applications.
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This paper revisits the long-held assumption that reactive replanning requires updating existing plans. It shows that the incremental planning problem can alternatively be solved more efficiently as a series of independent problems using fast almost-surely asymptotically optimal (ASAO) planning algorithms. These ASAO algorithms quickly find an initial solution and converge towards an optimal solution which allows them to find consistent global plans in the presence of changing obstacles without requiring explicit plan reuse. This is demonstrated with simulated experiments where Effort Informed Trees (EIT*) finds shorter median solution paths than the tested reactive planning algorithms and is further validated using Asymptotically Optimal RRT-Connect (AORRTC) on a real-world planning problem on a robot arm.},
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year = 2025,
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eprint = {2510.21074},
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archivePrefix = {arXiv},
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primaryClass = {cs.RO},
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pdf = {https://arxiv.org/abs/2510.21074},
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projects = {realtime},
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note = {Under Review},
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abbr = {ARXIV},
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video = {https://www.youtube.com/watch?v=XaZrFy8wGZs},
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preview = {from_scratch.png}
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}
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@misc{mao2025cde,
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title = {CDE: Concept-Driven Exploration for Reinforcement Learning},
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author = {Le Mao and Andrew H. Liu and Renos Zabounidis and Zachary Kingston and Joseph Campbell},

_data/coauthors.yml

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member: true
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url: andy
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"ruan":
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- firstname: ["Joseph"]
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member: true
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url: jlruan
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"campbell":
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- firstname: ["Joseph"]
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url: https://joe-campbell.github.io/website/

_layouts/member.liquid

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<div class="post">
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<header class="post-header">
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<h1 class="post-title">{{ page.first_name }} {{ page.last_name }}
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<h1 class="post-title">{{ page.title }}
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{% if page.alumni %}
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(Alumni)
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{% endif %}

_members/akshaya.md

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---
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layout: member
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title: Akshaya
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title: Akshaya Agrawal
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first_name: Akshaya
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last_name: Agrawal
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pronouns: she/her
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group_rank: 2
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---
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I am a robotics researcher working on Multi-Robot Motion Planning. As a robotics Ph.D. student at Oregon State University, I am advised and mentored by Geoff Hollinger and Zak Kingston. My passion is to enable a team of robots to perform tasks that are larger than us (humans).
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I am a robotics researcher working on Multi-Robot Motion Planning. As a robotics Ph.D. student at Oregon State University, I am advised and mentored by Geoff Hollinger and Zak Kingston. My passion is to enable a team of robots to perform tasks that are larger than us (humans).

_members/andy_niu.md

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layout: member
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title: Under Graduate
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title: Andy Niu
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first_name: Andy
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last_name: Niu
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pronouns: he/him

_members/austin.md

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title: Austin
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title: Austin J. Garrett
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first_name: Austin J.
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last_name: Garrett
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---
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I am an incoming PhD student at the CoMMA Lab at Purdue University, advised by Dr. Zachary Kingston. My research aims to develop robotic agents that can reason about uncertainty while incrementally refining probabilistic models of motion.
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I am a first year PhD student at the CoMMA Lab at Purdue University, advised by Dr. Zachary Kingston. My research aims to develop robotic agents that can reason about uncertainty while incrementally refining probabilistic models of motion.
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To this end, I bring probabilistic programming to robotics. Probabilistic programming is an emerging paradigm for building inference kernels that automatically construct particle-based approximations of complex, multimodal posteriors. I hypothesize that by leveraging these kernels, robotic systems can generalize trajectory inference across discontinuities in dynamics and environments—scenarios where gradient-based methods alone often fail.
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_members/jlruan.md

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layout: member
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title: Joseph Ruan
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first_name: Joey
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title: Joey Ruan
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first_name: Joseph
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last_name: Ruan
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pronouns: he/they
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github: "jlruan"
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group: Undergraduate Students
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group_rank: 5
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---
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Hi! I'm Joey, a Mechanical Engineering student with an interest in autonomous systems, controls, and robotics and a minor in economics. I've done a lot of things from designing a subterranean robot squid for the USDA to working on computational behavioral economics models for Wall Street researchers. I'll be working on thermal solutions for AMD for the summer of 2025 but if you're working on cool stuff and have an opening in the future LMK!
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Hi! I'm Joey, a Mechanical Engineering student with an interest in autonomous systems, controls, and robotics and a minor in economics. I've done a lot of things from designing a subterranean robot squid for the USDA to working on computational behavioral economics models for Wall Street researchers. I'll be working on thermal solutions for AMD for the summer of 2025 but if you're working on cool stuff and have an opening in the future LMK!

_members/shrutheesh.md

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title: Shrutheesh R. Iyer
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first_name: Shrutheesh R.
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last_name: Iyer
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_members/talha.md

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title: S. Talha Bukhari
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first_name: S. Talha
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last_name: Bukhari
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_pages/members.md

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{% capture member_image %}assets/img/people/{{ member.image }}{% endcapture %}
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{% include figure.liquid loading="lazy" path=member_image class="student-image" alt=member.first_name %}
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<div class="student-name">{{ member.first_name }} {{ member.last_name }}</div>
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{% include figure.liquid loading="lazy" path=member_image class="student-image" alt=member.title %}
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<div class="student-name">{{ member.title }}</div>
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{% if member.pronouns %}<div class="student-subtitle">({{ member.pronouns }})</div>{% endif %}
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</a>
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<div class="team col-7 col-xs-9 col-sm-9 col-md-10">
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<a href="{{ member.url }}">
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<h5 class="card-title">{{ member.title }}</h5>
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{% if member.position %}<h6 class="card-subtitle mb-2 text-muted">{{ member.position }}</h6>{% endif %}
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{% if member.pronouns %}<h6 class="card-subtitle mb-2 text-muted">({{ member.pronouns }})</h6>{% endif %}
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<p class="card-text">

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