Organizational Unit:
Healthcare Robotics Lab

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Author: Jain, Advait × Author: Nguyen, Hai × Has files: Yes ×

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    The complex structure of simple devices: A survey of trajectories and forces that open doors and drawers
    (Georgia Institute of Technology, 2010-09) Jain, Advait ; Nguyen, Hai ; Rath, Mrinal ; Okerman, Jason ; Kemp, Charles C.
    Instrumental activities of daily living (IADLs) involve physical interactions with diverse mechanical systems found within human environments. In this paper, we describe our efforts to capture the everyday mechanics of doors and drawers, which form an important sub-class of mechanical systems for IADLs. We also discuss the implications of our results for the design of assistive robots. By answering questions such as “How high are the handles of most doors and drawers?” and “What forces are necessary to open most doors and drawers?”, our approach can inform robot designers as they make tradeoffs between competing requirements for assistive robots, such as cost, workspace, and power. Using a custom motion/force capture system, we captured kinematic trajectories and forces while operating 29 doors and 15 drawers in 6 homes and 1 office building in Atlanta, GA, USA. We also hand-measured the kinematics of 299 doors and 152 drawers in 11 area homes. We show that operation of these seemingly simple mechanisms involves significant complexities, including non-linear forces and large kinematic variation. We also show that the data exhibit significant structure. For example, 91.8% of the variation in the force sequences used to open doors can be represented using a 2-dimensional linear subspace. This complexity and structure suggests that capturing everyday mechanics may be a useful approach for improving the design of assistive robots.
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    A Clickable World: Behavior Selection Through Pointing and Context for Mobile Manipulation
    (Georgia Institute of Technology, 2008-09) Nguyen, Hai ; Jain, Advait ; Anderson, Cressel D. ; Kemp, Charles C.
    We present a new behavior selection system for human-robot interaction that maps virtual buttons overlaid on the physical environment to the robotpsilas behaviors, thereby creating a clickable world. The user clicks on a virtual button and activates the associated behavior by briefly illuminating a corresponding 3D location with an off-the-shelf green laser pointer. As we have described in previous work, the robot can detect this click and estimate its 3D location using an omnidirectional camera and a pan/tilt stereo camera. In this paper, we show that the robot can select the appropriate behavior to execute using the 3D location of the click, the context around this 3D location, and its own state. For this work, the robot performs this selection process using a cascade of classifiers. We demonstrate the efficacy of this approach with an assistive object-fetching application. Through empirical evaluation, we show that the 3D location of the click, the state of the robot, and the surrounding context is sufficient for the robot to choose the correct behavior from a set of behaviors and perform the following tasks: pick-up a designated object from a floor or table, deliver an object to a designated person, place an object on a designated table, go to a designated location, and touch a designated location with its end effector.
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    EL-E: An Assistive Mobile Manipulator that Autonomously Fetches Objects from Flat Surfaces
    (Georgia Institute of Technology, 2008-03-12) Nguyen, Hai ; Anderson, Cressel D. ; Trevor, Alexander J. B. ; Jain, Advait ; Xu, Zhe ; Kemp, Charles C.
    Objects within human environments are usually found on flat surfaces that are orthogonal to gravity, such as floors, tables, and shelves. We first present a new assistive robot that is explicitly designed to take advantage of this common structure in order to retrieve unmodeled, everyday objects for people with motor impairments. This compact, stati- cally stable mobile manipulator has a novel kinematic and sensory configuration that facilitates autonomy and human- robot interaction within indoor human environments. Sec- ond, we present a behavior system that enables this robot to fetch objects selected with a laser pointer from the floor and tables. The robot can approach an object selected with the laser pointer interface, detect if the object is on an elevated surface, raise or lower its arm and sensors to this surface, and visually and tacitly grasp the object. Once the object is acquired, the robot can place the object on a laser des- ignated surface above the floor, follow the laser pointer on the floor, or deliver the object to a seated person selected with the laser pointer. Within this paper we present initial results for object acquisition and delivery to a seated, able- bodied individual. For this test, the robot succeeded in 6 out of 7 trials (86%).