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Kemp,
Charles C.
Kemp,
Charles C.
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ItemWhole-arm Tactile Sensing for Beneficial and Acceptable Contact During Robotic Assistance(Georgia Institute of Technology, 2013-06) Grice, Phillip M. ; Killpack, Marc D. ; Jain, Advait ; Vaish, Sarvagya ; Hawke, Jeffrey ; Kemp, Charles C.Many assistive tasks involve manipulation near the care-receiver's body, including self-care tasks such as dressing, feeding, and personal hygiene. A robot can provide assistance with these tasks by moving its end effector to poses near the care-receiver's body. However, perceiving and maneuvering around the care-receiver's body can be challenging due to a variety of issues, including convoluted geometry, compliant materials, body motion, hidden surfaces, and the object upon which the body is resting (e.g., a wheelchair or bed). Using geometric simulations, we first show that an assistive robot can achieve a much larger percentage of end-effector poses near the care-receiver's body if its arm is allowed to make contact. Second, we present a novel system with a custom controller and whole-arm tactile sensor array that enables a Willow Garage PR2 to regulate contact forces across its entire arm while moving its end effector to a commanded pose. We then describe tests with two people with motor impairments, one of whom used the system to grasp and pull a blanket over himself and to grab a cloth and wipe his face, all while in bed at his home. Finally, we describe a study with eight able-bodied users in which they used the system to place objects near their bodies. On average, users perceived the system to be safe and comfortable, even though substantial contact occurred between the robot's arm and the user's body.
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ItemTactile Sensing over Articulated Joints with Stretchable Sensors(Georgia Institute of Technology, 2013-04) Bhattacharjee, Tapomayukh ; Jain, Advait ; Vaish, Sarvagya ; Killpack, Marc D. ; Kemp, Charles C.Biological organisms benefit from tactile sensing across the entire surfaces of their bodies. Robots may also be able to benefit from this type of sensing, but fully covering a robot with robust and capable tactile sensors entails numerous challenges. To date, most tactile sensors for robots have been used to cover rigid surfaces. In this paper, we focus on the challenge of tactile sensing across articulated joints, which requires sensing across a surface whose geometry varies over time. We first demonstrate the importance of sensing across joints by simulating a planar arm reaching in clutter and finding the frequency of contact at the joints. We then present a simple model of how much a tactile sensor would need to stretch in order to cover a 2 degree-of-freedom (DoF) wrist joint. Next, we describe and characterize a new tactile sensor made with stretchable fabrics. Finally, we present results for a stretchable sleeve with 25 tactile sensors that covers the forearm, 2 DoF wrist, and end effector of a humanoid robot. This sleeve enabled the robot to reach a target in instrumented clutter and reduce contact forces.
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ItemTowards an Assistive Robot that Autonomously Performs Bed Baths for Patient Hygiene(Georgia Institute of Technology, 2010-10) King, Chih-Hung ; Chen, Tiffany L. ; Jain, Advait ; Kemp, Charles C.This paper describes the design and implementation of a behavior that allows a robot with a compliant arm to perform wiping motions that are involved in bed baths. A laser-based operator-selection interface enables an operator to select an area to clean, and the robot autonomously performs a wiping motion using equilibrium point control. We evaluated the performance of the system by measuring the ability of the robot to remove an area of debris on human skin. We tested the performance of the behavior algorithm by commanding the robot to wipe off a 1-inch square area of debris placed on the surface of the upper arm, forearm, thigh, and shank of a human subject. Using image processing, we determined the hue content of the debris and used this representation to determine the percentage of debris that remained on the arm after the robot completed the task. In our experiments, the robot removed most of the debris (>96%) on four parts of the limbs. In addition, the robot performed the wiping task using relatively low force (<;3 N).
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ItemOperating articulated objects based on experience(Georgia Institute of Technology, 2010-10) Sturm, Jürgen ; Jain, Advait ; Stachniss, Cyrill ; Kemp, Charles C. ; Burgard, WolframMany tasks that would be of benefit to users in domestic environments require that robots manipulate articulated objects such as doors and drawers. In this paper, we present a novel approach that simultaneously estimates the kinematic model of an articulated object based on the trajectory described by the robot's end effector, and uses this model to predict the future trajectory of the end effector. One advantage of our approach is that the robot can directly use these predictions to generate an equilibrium point control path for operating the mechanism. Additionally, our approach can improve these predictions based on previously learned articulation models. We have implemented and tested our approach on a real mobile manipulator. Through 40 trials, we show that the robot can reliably open various household objects, including cabinet doors, sliding doors, office drawers, and a dishwasher. Furthermore, we demonstrate that using the information from previous interactions as a prior significantly improves the prediction accuracy.
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ItemThe 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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ItemPulling Open Doors and Drawers: Coordinating an Omni-directional Base and a Compliant Arm with Equilibrium Point Control(Georgia Institute of Technology, 2010-05) Jain, Advait ; Kemp, Charles C.Previously, we have presented an implementation of impedance control inspired by the Equilibrium Point Hypothesis that we refer to as equilibrium point control (EPC). We have demonstrated that EPC can enable a robot in a fixed position to robustly pull open a variety of doors and drawers, and infer their kinematics without detailed prior models. In this paper, we extend this framework to support autonomous motion of the robot's omni-directional base both before and during pulling. With our new methods, we show that the robot can autonomously approach and open doors and drawers for which only the location and orientation of the handle have been provided. We also demonstrate that EPC can coordinate the movement of the robot's omni-directional base and compliant arm while pulling open a door or drawer, which leads to significantly improved performance. Through 40 trials with 10 different doors and drawers, we empirically demonstrated the robustness of the system. The robot succeeded in 37 out of 40 trials, and had no more than a single failure for any particular door or drawer.