93 citations · 150 across the 14 of their papers we have counts for
16 papers
Task and Motion Planning for Execution in the Real
Tianyang Pan, Rahul Shome, Lydia E. Kavraki
Task and motion planning represents a powerful set of hybrid planning methods that combine reasoning over discrete task domains and continuous motion generation. Traditional reason…
Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning
Yoonchang Sung, Rahul Shome, Peter Stone
This paper explores general multi-robot task and motion planning, where multiple robots in close proximity manipulate objects while satisfying constraints and a given goal. In part…
Robots as AI Double Agents: Privacy in Motion Planning
Rahul Shome, Zachary Kingston, Lydia E. Kavraki
Robotics and automation are poised to change the landscape of home and work in the near future. Robots are adept at deliberately moving, sensing, and interacting with their environ…
Task-driven Perception and Manipulation for Constrained Placement of Unknown Objects
Chaitanya Mitash, Rahul Shome, Bowen Wen +2
Recent progress in robotic manipulation has dealt with the case of previously unknown objects in the context of relatively simple tasks, such as bin-picking. Existing methods for m…
Synchronized Multi-Arm Rearrangement Guided by Mode Graphs with Capacity Constraints
Rahul Shome, Kostas E. Bekris
Solving task planning problems involving multiple objects and multiple robotic arms poses scalability challenges. Such problems involve not only coordinating multiple high-DoF arms…
That and There: Judging the Intent of Pointing Actions with Robotic Arms
Malihe Alikhani, Baber Khalid, Rahul Shome +3
Collaborative robotics requires effective communication between a robot and a human partner. This work proposes a set of interpretive principles for how a robotic arm can use point…
Asymptotically Optimal Sampling-based Planners
Kostas E. Bekris, Rahul Shome
An asymptotically optimal sampling-based planner employs sampling to solve robot motion planning problems and returns paths with a cost that converges to the optimal solution cost,…
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…
Pushing the Boundaries of Asymptotic Optimality in Integrated Task and Motion Planning
Rahul Shome, Daniel Nakhimovich, Kostas E. Bekris
Integrated task and motion planning problems describe a multi-modal state space, which is often abstracted as a set of smooth manifolds that are connected via sets of transitions s…
Tight Robot Packing in the Real World: A Complete Manipulation Pipeline with Robust Primitives
Rahul Shome, Wei N. Tang, Changkyu Song +5
Many order fulfillment applications in logistics, such as packing, involve picking objects from unstructured piles before tightly arranging them in bins or shipping containers. Des…
Fast, High-Quality Dual-Arm Rearrangement in Synchronous, Monotone Tabletop Setups
Rahul Shome, Kiril Solovey, Jingjin Yu +2
Rearranging objects on a planar surface arises in a variety of robotic applications, such as product packaging. Using two arms can improve efficiency but introduces new computation…
Fast, Anytime Motion Planning for Prehensile Manipulation in Clutter
Andrew Kimmel, Rahul Shome, Zakary Littlefield +1
Many methods have been developed for planning the motion of robotic arms for picking and placing, ranging from local optimization to global search techniques, which are effective f…
Scalable Asymptotically-Optimal Multi-Robot Motion Planning
Andrew Dobson, Kiril Solovey, Rahul Shome +2
Finding asymptotically-optimal paths in multi-robot motion planning problems could be achieved, in principle, using sampling-based planners in the composite configuration space of…
A Dataset for Improved RGBD-based Object Detection and Pose Estimation for Warehouse Pick-and-Place
Colin Rennie, Rahul Shome, Kostas E. Bekris +1
An important logistics application of robotics involves manipulators that pick-and-place objects placed in warehouse shelves. A critical aspect of this task corre- sponds to detect…
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…