Hugging Face Trending Papers
Reward-Guided RRT* for Budgeted Task and Motion Planning
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arXiv AI
Oct 27
Reward-Guided RRT* for Budgeted Task and Motion Planning
Reward‑Guided RRT* is a sampling‑based framework that builds budget‑feasible robotic missions by iteratively selecting rewarding locations and planning motions directly in continuous state space, without a pre‑computed task‑transition graph. The method uses reward‑guided RRT* searches and a return‑feasibility check to ensure each task can be visited within the travel budget. Experiments on increasingly complex obstacle environments and task counts show solutions comparable to VNS‑PRM* while sampling far fewer states, and the framework is extended to Dubins steering and validated on a scaled car‑like robot in CoppeliaSim.
arXiv AI
Sep 1
SGE: Semantically-Guided Exploration for Unstructured Environments via Image-Space Waypoint Sampling
arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic...
arXiv AI
Jun 6
From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution
arXiv:2604. 12474v3 Announce Type: replace-cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission.
arXiv AI
Jul 2
Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets
arXiv:2607. 00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, which is challenging in continuous spaces when feasible regions are transient and geometrically constrained.
arXiv Machine Learning
Aug 26
NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments
arXiv:2608.24485v1 Announce Type: cross Abstract: Automated parking commonly assumes marked slots and short approach maneuvers. Delivery and service vehicles, however, may need to reach an operator-s...
arXiv AI
Jul 1
CoReLIN: Constraint-based Reasoning for Zero-shot Lifelong Interactive Navigation
arXiv:2602. 20055v2 Announce Type: replace-cross Abstract: Robot navigation typically assumes an obstacle-free path exists between start and goal.