Christopher Lee

Online, interactive learning of gestures for human/robot interfaces

We have developed a gesture recognition system, based on hidden Markov models, which can interactively recognize gestures and perform online learning of new gestures. In addition, it is able to update its model of a gesture iteratively with each example it recognizes. This system has demonstrated reliable recognition of 14 different gestures after only one or two examples of each. The system is currently interfaced to a Cyberglove for use in recognition of gestures from the sign language alphabet. The system is being implemented as part of an interactive interface for robot teleoperation and programming by example.

A dynamic coupling index for underactuated manipulators

In recent years, researchers have been dedicated to the study of underactuated manipulators, which have more joints than control actuators. In previous work, researchers always assumed that there was enough dynamic coupling between the active and the passive joints of the manipulator for it to be possible to control the position of the passive joints via the dynamic coupling. In this work, the authors aim to develop an index to measure the dynamic coupling, so as to address when control of the under-actuated system is possible, and how the motion and robot configuration can be designed. We discuss extensively the nature of the dynamic coupling and of the proposed coupling index, and their applications in the analysis and design of underactuated systems, through a detailed mathematical analysis and several illustrative examples.

Dynamic coupling of underactuated manipulators

In recent years, researchers have been dedicated to the study of underactuated manipulators which have more joints than control actuators. In previous works, assumptions were made as to the existence of enough dynamic coupling between the active and the passive joints of the manipulator for it to be possible to control the position of the passive joints via the dynamic coupling. In this work, the authors aim to develop an index to measure the dynamic coupling, so as to address when control of the underactuated system is possible, and how the motion and robot configuration can be designed. The authors discuss extensively the nature of the dynamic coupling and of the proposed coupling index, and their applications in the analysis and design of underactuated systems, and in control and planning of robot motion configuration.

Experimental study of an underactuated manipulator

Underactuated manipulators are a class of robotic mechanisms where passive joints are present. By controlling only the motion of the active joints, it is possible to control the entire system. Our goal is to develop control schemes using both classical nonlinear and modem learning techniques for underactuated manipulators. To examine the validity of the approaches, we developed an experimental setup known as U-ARM, or underactuated robot manipulator. In this paper we present the hardware development, dynamic parameters, control software and experimental results of real-time control of the U-ARM.

Trajectory fitting with smoothing splines using velocity information

We present a derivation for a spline smoother which takes into account local velocity information. This smoother is well suited for finding a best-fit trajectory from multiple example trajectories and is thus useful in applications such as programming by demonstration and online gesture recognition for teleoperation. Currently available smoothers are designed to consider only position information and not local velocity information, and are thus less suited for smoothing trajectories over time of dynamic systems.

A separable combination of wheeled rover and arm mechanism: (DM)/sup 2/

We present a novel mobile manipulator concept called the dual-use mobile detachable manipulator, or (DM)/sup 2/, for early construction and maintenance tasks in lunar stations. The robot consists of a wheeled rover, or mobile base and a detachable manipulator arm. The arm is symmetric, with a gripper at each end. When the arm attaches to the mobile base by grasping a handle with one of its grippers, the robot becomes a mobile manipulator and can perform exploration tasks such as collecting soil samples, surveying the lunar surface, and transporting tools and supplies. When the robot nears a lunar center structure such as a manufacturing center or a fuel tank, the manipulator arm can detach from the base and walk hand-over-hand, by grasping a series of handles on the structure, to perform tasks such as structure inspection, parts delivery, and simple assembly tasks. The paper discusses the concept and its advantages, the system under development, and its software architecture.

Message-Based Evaluation in Scheme for High-Level Robot Control

In this paper, we present a method for high-level control of robots whose low-level software is based on dynamically reconfigurable, reusable real-time software modules. Our approach is to use an embedded interpreter for a general-purpose programming language to direct the operation of the low-level modules toward meeting the task-level goals of the robot. To this end, we present RSK, a virtual-machine kernel implementing a Scheme interpreter capable of hard real-time operation, and employing a method of code execution we call “message-based evaluation” (MBE) . MBE is a novel combination of a traditional code execution model and a message-passing architecture, which simplifies the process of writing code for managing the robots reconfigurable subsystem.

Reduced-dimension representations of human performance data for human-to-robot skill transfer

Despite the large amount of research currently directed toward programming robots by demonstration, a significant problem with this method of human-to-robot skill transfer has not yet been addressed: developing representations of human performances which isolate the intrinsic dimensions of the performances (and thus the skills which guide them) within high-dimensional, raw human performance data. In this paper we propose the use of three methods for representing high-dimensional human performance data within lower-dimensional spaces: principal component analysis (PCA), nonlinear principal component analysis (NLPCA), and sequential nonlinear principal component analysis (SNLPCA). We compare the appropriateness of these methods for modeling a simple human grasping operation.

A Community-Driven Workflow Recommendations and Reuse Infrastructure

NASA Earth Exchange (NEX) aims to provide a platform to enable and facilitate scientific collaboration and knowledge sharing in the Earth sciences, as current satellite measurements rapidly magnify the accumulation of more than 40 years of NASA datasets. One of the main objectives of NEX is to help Earth scientists leverage and reuse various data processing software modules developed by their peers, in order to quickly run value-added executable experiments (workflows). Toward this goal, this paper reports our efforts of leveraging social network analysis to intelligently extract hidden information from data processing workflows. By modeling Earth science workflow modules as social entities and their dependencies as social relationships, this research opens up new vistas for applying social science to facilitate software reuse and distributed workflow development. As a proof of concept, a prototyping system has been developed as a plug-in to the NEX workflow design and management system (VisTrails) to aid Earth scientists in discovering and reusing workflow modules and extending them to solve more complex science problems.

Climate Analytics Workflow Recommendation as a Service - Provenance-Driven Automatic Workflow Mashup

Existing scientific workflow tools, created by computer scientists, require that domain scientists meticulously design their multi-step experiments before analyzing data. However, this is oftentimes contradictory to a domain scientists routine of conducting research and exploration. This paper presents a novel way to resolve this dispute, in the context of service-oriented science. After scrutinizing how Earth scientists conduct data analytics research in their daily work, a provenance model is developed to record their activities. Reverse-engineering the provenance, a technology is developed to automatically generate workflows for scientists to review and revise, supported by a Petri nets-based workflow verification instrument. In addition, dataset is proposed to be treated as first-class citizen to drive the knowledge sharing and recommendation. A data-centric repository infrastructure is established to catch richer provenance to further facilitate collaboration in the science community. In this way, we aim to revolutionize computer-supported Earth science.