5 accepted papers
3D object reconfiguration encompasses common robot manipulation tasks in which a set of objects must be moved through a series of physically feasible state changes into a desired final configuration. Object reconfiguration is challenging to solve in general, as it requires efficient reasoning about…
Sampling-based motion planners are widely used for motion planning with high- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dof</small> robots. These planners generally rely on a uniform distribution to explore the search space. Recent work has explore
This letter presents GAMMA, a general motion prediction model that enables large-scale real-time simulation and planning for autonomous driving. GAMMA models <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">heterogeneous</i> , <italic xmlns:mml="http:
The partially observable Markov decision process (POMDP) is a principled general framework for robot decision making under uncertainty; but POMDP planning suffers from high computational complexity; when long-term planning is required. While temporally-extended macro-actions help to cut down the eff…
Autonomous driving in an unregulated urban crowd is an outstanding challenge, especially, in the presence of many aggressive, high-speed traffic participants. This paper presents SUMMIT, a high-fidelity simulator that facilitates the development and testing of crowd-driving algorithms. By leveraging…