21 citations · 115 across the 27 of their papers we have counts for
55 papers
Leveraging Experience in Lazy Search
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots +1
Lazy graph search algorithms are efficient at solving motion planning problems where edge evaluation is the computational bottleneck. These algorithms work by lazily computing the…
Desk Organization: Effect of Multimodal Inputs on Spatial Relational Learning
Ryan Rowe, Shivam Singhal, Daqing Yi +2
For robots to operate in a three dimensional world and interact with humans, learning spatial relationships among objects in the surrounding is necessary. Reasoning about the state…
Lazy Lifelong Planning for Efficient Replanning in Graphs with Expensive Edge Evaluation
Jaein Lim, Siddhartha Srinivasa, Panagiotis Tsiotras
We present an incremental search algorithm, called Lifelong-GLS, which combines the vertex efficiency of Lifelong Planning A* (LPA*) and the edge efficiency of Generalized Lazy Sea…
Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
Aditya Mandalika, Rosario Scalise, Brian Hou +2
Sampling-based motion planners rely on incremental densification to discover progressively shorter paths. After computing feasible path between start and goal , the…
Learning Online from Corrective Feedback: A Meta-Algorithm for Robotics
Matthew Schmittle, Sanjiban Choudhury, Siddhartha S. Srinivasa
A key challenge in Imitation Learning (IL) is that optimal state actions demonstrations are difficult for the teacher to provide. For example in robotics, providing kinesthetic dem…
Faster Policy Learning with Continuous-Time Gradients
Samuel Ainsworth, Kendall Lowrey, John Thickstun +2
We study the estimation of policy gradients for continuous-time systems with known dynamics. By reframing policy learning in continuous-time, we show that it is possible construct…