5 papers · 1 filter
Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking
Alex Beaudin, Hanna Krasowski, Kartik Nagpal +3
Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing approaches typically rely on h…
RHO: Your Coding Agent is Secretly a Roboticist
Karim Elmaaroufi, Justin Svegliato, Sarunas Kalade +3
Code-as-Policies (CaP) has shown that large language models (LLMs) can write code to solve robotics tasks by composing perception, planning, and control primitives. Recent CaP syst…
ScenicRules: An Autonomous Driving Benchmark with Multi-Objective Specifications and Abstract Scenarios
Kevin Kai-Chun Chang, Ekin Beyazit, Alberto Sangiovanni-Vincentelli +2
Developing autonomous driving systems for complex traffic environments requires balancing multiple objectives, such as avoiding collisions, obeying traffic rules, and making effici…
Learning Affordances at Inference-Time for Vision-Language-Action Models
Ameesh Shah, William Chen, Adwait Godbole +3
Solving complex real-world control tasks often takes multiple tries: if we fail at first, we reflect on what went wrong, and change our strategy accordingly to avoid making the sam…
MRTA-Sim: A Modular Simulator for Multi-Robot Allocation, Planning, and Control in Open-World Environments
Victoria Marie Tuck, Hardik Parwana, Pei-Wei Chen +5
This paper introduces MRTA-Sim, a Python/ROS2/Gazebo simulator for testing approaches to Multi-Robot Task Allocation (MRTA) problems on simulated robots in complex, indoor environm…