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

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

Motion Planning with incomplete scene information

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

Neural Network Pruning - A review

Review of methods to prune neural networks

Robust Motion Planning under Sensing Uncertainty

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