Tufts University, human-robot interaction - Computer Science. PhD in-progress.
Supervising Faculty: Elaine Schaertl Short
Contingency Detection
Contingency detection between a human participant and multiple agents in a simulated environment. An online human-subjects study platform was implemented for remote studies. In this environment multiple agents interact with toys and a participant. Temporal pattern analysis was conducted on extracted features to determine which agent held the participants attention. Short Paper. Study Environment.
Ongoing work uses mutual information as a proxy for contingency between agent and human behavior distributions. Full paper pending.
Socially Assistive Robotics
Robot arm trajectory modified by simple human feedback for socially assistive robotics. Preset trajectory represented by Dynamic Motion Primitives (DMPs). Trajectory was modified by adjusting DMP basis functions in line with binary human feedback.
Reinforcement Learning
Supervising Faculty: Jivko Sinapov
Hierarchical Reinforcement Learning multi-step tasks. Sub-policies and a Top-level DQN were trained to collect materials and make a goal object in a multi-step Minecraft task. Ongoing work uses soft-actor critic sub-policies to adapt to novel environmental changes in either the state, transitions or rewards.
Human-criticized reinforcement learning for modifying a simulated arm trajectory. Goal achievement with a TAMER-like algorithm to learn stylistic flare without sacrificing goal achievement. Tiled state representation. Python.
Anomaly Detection
Supervising Faculty: Matthias Scheutz
Improving task performance of a multi-agent team with anomaly detection. Task performance of a two-agent was statistically analyzed to detect non-directly observable equipment failures. Task success rates could be improved through role reallocation if systematic anomalies were detected. Full Paper.
National Robotics Engineering Center, Carnegie Mellon, Pittsburgh, Pa. Summer ‘13
Orange Grove Laser Analysis
Analyzed 3D laser scans of 150 acre orange groves to extract features about the tree canopies. Performed regression analysis on extracted features and analyzed correlation to orange yield. Visualizing results. Matlab. Paper.
Deep Learning Neural Net Configuration
Implemented artificial neural network package to test deep learning performance on obstacle recognition in farm environment. The ANN was fed labeled data of images with and without farm obstacles. Different configurations of layers and nodes were tested. Matlab.
Colby College, Waterville, Me. Summer ’10
Humanoid Robot Vision and Interaction
Developed interactive games for a small humanoid robot to play with children. The work was done as part of an NSF grant aimed at increasing young children’s exposure to STEM. Simon Says and Red Light Green Light were implemented using motion and face detection software. Work was presented to NSF advisory/funding board. C.