93 citations · 101 across the 5 of their papers we have counts for
5 papers
Towards Learning Efficient Maneuver Sets for Kinodynamic Motion Planning
Aravind Sivaramakrishnan, Zakary Littlefield, Kostas E. Bekris
Planning for systems with dynamics is challenging as often there is no local planner available and the only primitive to explore the state space is forward propagation of controls.…
Anytime Multi-arm Task and Motion Planning for Pick-and-Place of Individual Objects via Handoffs
Rahul Shome, Kostas E. Bekris
Automation applications are pushing the deployment of many high DoF manipulators in warehouse and manufacturing environments. This has motivated many efforts on optimizing manipula…
dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planning
Rahul Shome, Kiril Solovey, Andrew Dobson +2
Many exciting robotic applications require multiple robots with many degrees of freedom, such as manipulators, to coordinate their motion in a shared workspace. Discovering high-qu…
Similar Part Rearrangement With Pebble Graphs
Athanasios Krontiris, Rahul Shome, Andrew Dobson +3
This work proposes a method for effectively computing manipulation paths to rearrange similar objects in a cluttered space. The solution can be used to place similar products in a…
Sampling-based Roadmap Planners are Probably Near-Optimal after Finite Computation
Andrew Dobson, George V. Moustakides, Kostas E. Bekris
Sampling-based motion planners have proven to be efficient solutions to a variety of high-dimensional, geometrically complex motion planning problems with applications in several d…