Projects

Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty

Safe motion planning approach for noisy sensor measurement representation of the environment using a stochastic neural implicit representation and chance constrained optimization.

Optimal Grasps and Placements for Task and Motion Planning in Clutter

Task and Motion Planning framework that combines a SMT-based task planner, sampling-based motion planners and a novel optimization-based grounder to find optimal object placement locations and robot grasps for cluttered environments.

MotionBenchMaker A Tool to Generate and Benchmark Motion Planning Datasets

Open source tool to generate benchmarking datasets for robot manipulation problems.

Human-Guided Motion Planning in Partially Observable Environments

Human-in-the-loop algorithm to compute joint-space trajectories for high-DoF robots under partial observability

Motion Planning with incomplete scene information

A Fetch robot doing Motion Planning and executing a trajectory when the scene representation may be incomplete

Robust Motion Planning under Sensing Uncertainty

Optimization-based motion planning algorithm capable of incorporating sensing uncertainty for a variety of noise models

Can Theoretical Algorithms Efficiently Escape Saddle Points in Deep Learning?

Review of optimization algorithms that can escape saddle points in Deep Learning and some experimental results

Inverse Kinematics Robo Picasso

Solving the inverse kinematics problem for a FANUC S-500 robot and using it to draw a Mickey Mouse

Neural Network Pruning - A review

Review of methods to prune neural networks