6 papers
MOSAIC: Skill-Centric Manipulation Planning with Physics Simulation
Itamar Mishani, Yorai Shaoul, Maxim Likhachev
Planning long-horizon manipulation motions using a set of predefined skills is a central challenge in robotics; solving it efficiently could enable general-purpose robots to tackle…
Constant-Time Motion Planning with Manipulation Behaviors
Nayesha Gandotra, Itamar Mishani, Maxim Likhachev
Recent progress in contact-rich robotic manipulation has been striking, yet most deployed systems remain confined to simple, scripted routines. One of the key barriers is the lack…
Multi Graph Search for High-Dimensional Robot Motion Planning
Itamar Mishani, Maxim Likhachev
Efficient motion planning for high-dimensional robotic systems, such as manipulators and mobile manipulators, is critical for real-time operation and reliable deployment. Although…
Parallel Heuristic Search as Inference for Actor-Critic Reinforcement Learning Models
Hanlan Yang, Itamar Mishani, Luca Pivetti +2
Actor-Critic models are a class of model-free deep reinforcement learning (RL) algorithms that have demonstrated effectiveness across various robot learning tasks. While considerab…
SRMP: Search-Based Robot Motion Planning Library
Itamar Mishani, Yorai Shaoul, Ramkumar Natarajan +2
Motion planning is a critical component in any robotic system. Over the years, powerful tools like the Open Motion Planning Library (OMPL) have been developed, offering numerous mo…
Multi-Robot Motion Planning with Diffusion Models
Yorai Shaoul, Itamar Mishani, Shivam Vats +2
Diffusion models have recently been successfully applied to a wide range of robotics applications for learning complex multi-modal behaviors from data. However, prior works have mo…