100 citations · 173 across the 20 of their papers we have counts for
20 papers
Sampling-Based Motion Planning: A Comparative Review
Andreas Orthey, Constantinos Chamzas, Lydia E. Kavraki
Sampling-based motion planning is one of the fundamental paradigms to generate robot motions, and a cornerstone of robotics research. This comparative review provides an up-to-date…
Asymptotically Optimal Belief Space Planning in Discrete Partially-Observable Domains
Janis Eric Freund, Camille Phiquepal, Andreas Orthey +1
Robots often have to operate in discrete partially observable worlds, where the states of world are only observable at runtime. To react to different world states, robots need cont…
Fast-dRRT*: Efficient Multi-Robot Motion Planning for Automated Industrial Manufacturing
Andrey Solano, Arne Sieverling, Robert Gieselmann +1
We present Fast-dRRT*, a sampling-based multi-robot planner, for real-time industrial automation scenarios. Fast-dRRT* builds upon the discrete rapidly-exploring random tree (dRRT*…
Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces
Servet B. Bayraktar, Andreas Orthey, Zachary Kingston +2
Rearrangement puzzles are variations of rearrangement problems in which the elements of a problem are potentially logically linked together. To efficiently solve such puzzles, we d…
Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach
Ilyes Toumi, Andreas Orthey, Alexander von Rohr +1
Automated bin-picking is a prerequisite for fully automated manufacturing and warehouses. To successfully pick an item from an unstructured bin the robot needs to first detect poss…
Path-Tree Optimization in Discrete Partially Observable Environments using Rapidly-Exploring Belief-Space Graphs
Camille Phiquepal, Andreas Orthey, Nicolas Viennot +1
Robots often need to solve path planning problems where essential and discrete aspects of the environment are partially observable. This introduces a multi-modality, where the robo…