Matthew Klingensmith

TL;DR: CHOMP (covariant Hamiltonian optimization for motion planning), a method for trajectory optimization invariant to reparametrization, uses functional gradient techniques to iteratively improve the quality of an initial trajectory, optimizing a functional that trades off between a smoothness and an obstacle avoidance component.

TL;DR: CHISEL is a system for real-time housescale (300 square meter or more) dense 3D reconstruction onboard a Google Tango mobile device by using a dynamic spatially-hashed truncated signed distance field for mapping, and visual-inertial odometry for localization.

TL;DR: The software components of a robotics system designed to autonomously grasp objects and perform dexterous manipulation tasks with only high-level supervision are described and performance results for object grasping and complex manipulation tasks of in-house tests and of an independent evaluation team are presented.

TL;DR: This work develops new methods based on adaptive submodularity for selecting a sequence of information gathering actions online by drawing an explicit connection to submodular, and demonstrates the effectiveness of these methods in simulation and on a robot.

TL;DR: This work reduces the simultaneous optimization of pregrasp and transport trajectories to minimize overall cost to an optimization of the transport trajectory with start-point costs and shows how to use physically realistic planners to compute the cost of bringing the object to these start-points.