Area of research
Control and Systems Engineering · Computer Vision and Pattern Recognition
Research interest
Research interests include Robot Manipulation and Learning, Robotic Path Planning Algorithms, Soft Robotics and Applications, and Robotics and Sensor-Based Localization.
Planning Visual-Tactile Precision Grasps via Complementary Use of Vision and Touch
Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers
Correcting Robot Plans with Natural Language Feedback
StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objects
Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds
DefGraspSim: Physics-Based Simulation of Grasp Outcomes for 3D Deformable Objects
Attracting Conductive Nonmagnetic Objects With Rotating Magnetic Dipole Fields
Dexterous magnetic manipulation of conductive non-magnetic objects
Near-Optimal Area-Coverage Path Planning of Energy-Constrained Aerial Robots With Application in Autonomous Environmental Monitoring
Multifingered Grasp Planning via Inference in Deep Neural Networks: Outperforming Sampling by Learning Differentiable Models
Benchmarking In-Hand Manipulation
Multi-Fingered Active Grasp Learning
3D-Printing and Machine Learning Control of Soft Ionic Polymer-Metal Composite Actuators
Planning Multi-fingered Grasps as Probabilistic Inference in a Learned Deep Network
Modeling Grasp Type Improves Learning-Based Grasp Planning
Grip Stabilization of Novel Objects Using Slip Prediction
Relaxed-rigidity constraints: kinematic trajectory optimization and collision avoidance for in-grasp manipulation
First demonstration of simultaneous localization and propulsion of a magnetic capsule in a lumen using a single rotating magnet
Relaxed-Rigidity Constraints: In-Grasp Manipulation using Purely Kinematic Trajectory Optimization
Active tactile object exploration with Gaussian processes
Learning robot in-hand manipulation with tactile features
Evaluation of tactile feature extraction for interactive object recognition
I-Corps: Translation Potential of Mobile Manipulation for Object Retrieval in Rehabilitation Hospitals
Collaborative Research: CISE: Large: Executing Natural Instructions in Realistic Uncertain Worlds
Collaborative Research: NRI: FND: Learning Graph Neural Networks for Multi-Object Manipulation
CAREER: Improving Multi-Fingered Manipulation by Unifying Learning and Planning
CRII: RI: Enabling Manipulation of Object Collections via Self-Supervised Robot Learning