86 citations · 251 across the 40 of their papers we have counts for
13 papers · 1 filter
On the Effectiveness of Iterative Learning Control
Anirudh Vemula, Wen Sun, Maxim Likhachev +1
Iterative learning control (ILC) is a powerful technique for high performance tracking in the presence of modeling errors for optimal control applications. There is extensive prior…
AMRA*: Anytime Multi-Resolution Multi-Heuristic A*
Dhruv Mauria Saxena, Tushar Kusnur, Maxim Likhachev
Heuristic search-based motion planning algorithms typically discretise the search space in order to solve the shortest path problem. Their performance is closely related to this di…
Improved Soft Duplicate Detection in Search-Based Motion Planning
Nader Maray, Anirudh Vemula, Maxim Likhachev
Search-based techniques have shown great success in motion planning problems such as robotic navigation by discretizing the state space and precomputing motion primitives. However…
Multi-Objective Path-Based D* Lite
Zhongqiang Ren, Sivakumar Rathinam, Maxim Likhachev +1
Incremental graph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks. In this article, we are interested in…
Search-based Path Planning for a High Dimensional Manipulator in Cluttered Environments Using Optimization-based Primitives
Muhammad Suhail Saleem, Raghav Sood, Sho Onodera +3
In this work we tackle the path planning problem for a 21-dimensional snake robot-like manipulator, navigating a cluttered gas turbine for the purposes of inspection. Heuristic sea…
MPLP: Massively Parallelized Lazy Planning
Shohin Mukherjee, Sandip Aine, Maxim Likhachev
Lazy search algorithms have been developed to efficiently solve planning problems in domains where the computational effort is dominated by the cost of edge evaluation. The existin…