Tootfinder

The Architecture and Planning of Fascist New Towns in Sardinia
https://sah.org/2013/03/14/the-architecture-and-planning-of-fascist-new-towns-in-sardinia/

The Architecture and Planning of Fascist New Towns in Sardinia - Society of Architectural Historians
Ruth Lo documented three towns built between 1928 and 1938 on the island of Sardinia.

Task and Motion Planning for Humanoid Loco-manipulation
Michal Ciebielski, Victor Dh\'edin, Majid Khadiv
https://arxiv.org/abs/2508.14099 https://arxiv…

Task and Motion Planning for Humanoid Loco-manipulation
This work presents an optimization-based task and motion planning (TAMP) framework that unifies planning for locomotion and manipulation through a shared representation of contact modes. We define symbolic actions as contact mode changes, grounding high-level planning in low-level motion. This enables a unified search that spans task, contact, and motion planning while incorporating whole-body dynamics, as well as all constraints between the robot, the manipulated object, and the environment. R…

LOOP: A Plug-and-Play Neuro-Symbolic Framework for Enhancing Planning in Autonomous Systems
Ronit Virwani, Ruchika Suryawanshi
https://arxiv.org/abs/2508.13371 https://

LOOP: A Plug-and-Play Neuro-Symbolic Framework for Enhancing Planning in Autonomous Systems
Planning is one of the most critical tasks in autonomous systems, where even a small error can lead to major failures or million-dollar losses. Current state-of-the-art neural planning approaches struggle with complex domains, producing plans with missing preconditions, inconsistent goals, and hallucinations. While classical planners provide logical guarantees, they lack the flexibility and natural language understanding capabilities needed for modern autonomous systems. Existing neuro-symbolic…

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI
Karin A. Olthof, Matteo Fusagli, Bianca G\"uttner, Tiziano Natali, Bram Westerink, Stefanie Speidel, Theo J. M. Ruers, Koert F. D. Kuhlmann, Andrey Zhylka
https://arxiv.org/abs/2508.14133

Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI
Background: The aim of this study was to develop and evaluate a deep learning-based automated segmentation method for hepatic anatomy (i.e., parenchyma, tumors, portal vein, hepatic vein and biliary tree) from the hepatobiliary phase of gadoxetic acid-enhanced MRI. This method should ease the clinical workflow of preoperative planning. Methods: Manual segmentation was performed on hepatobiliary phase MRI scans from 90 consecutive patients who underwent liver surgery between January 2020 and O…

Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving
Bozhou Zhang, Jingyu Li, Nan Song, Li Zhang
https://arxiv.org/abs/2508.11488 https://

Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving
End-to-end autonomous driving has achieved remarkable advancements in recent years. Existing methods primarily follow a perception-planning paradigm, where perception and planning are executed sequentially within a fully differentiable framework for planning-oriented optimization. We further advance this paradigm through a perception-in-plan framework design, which integrates perception into the planning process. This design facilitates targeted perception guided by evolving planning objectives…

Improved Generalized Planning with LLMs through Strategy Refinement and Reflection
Katharina Stein, Nils Hodel, Daniel Fi\v{s}er, J\"org Hoffmann, Michael Katz, Alexander Koller
https://arxiv.org/abs/2508.13876

Improved Generalized Planning with LLMs through Strategy Refinement and Reflection
LLMs have recently been used to generate Python programs representing generalized plans in PDDL planning, i.e., plans that generalize across the tasks of a given PDDL domain. Previous work proposed a framework consisting of three steps: the LLM first generates a summary and then a strategy for the domain, both in natural language, and then implements that strategy as a Python program, that gets debugged on example planning tasks. In that work, only one strategy is generated and passed directly …

Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Jiming Ren, Xuan Lin, Roman Mineyev, Karen M. Feigh, Samuel Coogan, Ye Zhao
https://arxiv.org/abs/2508.13407

Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Task and motion planning under Signal Temporal Logic constraints is known to be NP-hard. A common class of approaches formulates these hybrid problems, which involve discrete task scheduling and continuous motion planning, as mixed-integer programs (MIP). However, in applications for bipedal locomotion, introduction of non-convex constraints such as kinematic reachability and footstep rotation exacerbates the computational complexity of MIPs. In this work, we present a method based on Benders D…

Can LLM Agents Solve Collaborative Tasks? A Study on Urgency-Aware Planning and Coordination
Jo\~ao Vitor de Carvalho Silva, Douglas G. Macharet
https://arxiv.org/abs/2508.14635

Can LLM Agents Solve Collaborative Tasks? A Study on Urgency-Aware Planning and Coordination
The ability to coordinate actions across multiple agents is critical for solving complex, real-world problems. Large Language Models (LLMs) have shown strong capabilities in communication, planning, and reasoning, raising the question of whether they can also support effective collaboration in multi-agent settings. In this work, we investigate the use of LLM agents to solve a structured victim rescue task that requires division of labor, prioritization, and cooperative planning. Agents operate …

FiReFly: Fair Distributed Receding Horizon Planning for Multiple UAVs
Nicole Fronda, Bardh Hoxha, Houssam Abbas
https://arxiv.org/abs/2508.14381 https://ar…

FiReFly: Fair Distributed Receding Horizon Planning for Multiple UAVs
We propose injecting notions of fairness into multi-robot motion planning. When robots have competing interests, it is important to optimize for some kind of fairness in their usage of resources. In this work, we explore how the robots' energy expenditures might be fairly distributed among them, while maintaining mission success. We formulate a distributed fair motion planner and integrate it with safe controllers in a algorithm called FiReFly. For simulated reach-avoid missions, FiReFly produc…

EAROL: Environmental Augmented Perception-Aware Planning and Robust Odometry via Downward-Mounted Tilted LiDAR
Xinkai Liang, Yigu Ge, Yangxi Shi, Haoyu Yang, Xu Cao, Hao Fang
https://arxiv.org/abs/2508.14554

EAROL: Environmental Augmented Perception-Aware Planning and Robust Odometry via Downward-Mounted Tilted LiDAR
To address the challenges of localization drift and perception-planning coupling in unmanned aerial vehicles (UAVs) operating in open-top scenarios (e.g., collapsed buildings, roofless mazes), this paper proposes EAROL, a novel framework with a downward-mounted tilted LiDAR configuration (20° inclination), integrating a LiDAR-Inertial Odometry (LIO) system and a hierarchical trajectory-yaw optimization algorithm. The hardware innovation enables constraint enhancement via dense ground point clo…