12 citations · 17 across the 4 of their papers we have counts for
6 papers · 1 filter
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…
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation
Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian +4
Sampling-based model-predictive control (MPC) is a promising tool for feedback control of robots with complex, non-smooth dynamics, and cost functions. However, the computationally…
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…
Differentiable Gaussian Process Motion Planning
Mohak Bhardwaj, Byron Boots, Mustafa Mukadam
Modern trajectory optimization based approaches to motion planning are fast, easy to implement, and effective on a wide range of robotics tasks. However, trajectory optimization al…
Data-driven Planning via Imitation Learning
Sanjiban Choudhury, Mohak Bhardwaj, Sankalp Arora +4
Robot planning is the process of selecting a sequence of actions that optimize for a task specific objective. The optimal solutions to such tasks are heavily influenced by the impl…
Learning Heuristic Search via Imitation
Mohak Bhardwaj, Sanjiban Choudhury, Sebastian Scherer
Robotic motion planning problems are typically solved by constructing a search tree of valid maneuvers from a start to a goal configuration. Limited onboard computation and real-ti…