Ultra high frequency (UHF) radio-frequency identification (RFID) for robot perception and mobile manipulation

Personal robots with autonomy, mobility, and manipulation capabilities have the potential to dramatically improve quality of life for various user populations, such as older adults and individuals with motor impairments. Unfortunately, unstructured environments present many challenges that hinder robot deployment in ordinary homes. This thesis seeks to address some of these challenges through a new robotic sensing modality that leverages a small amount of environmental augmentation in the form of Ultra High Frequency (UHF) Radio-Frequency Identification (RFID) tags. Previous research has demonstrated the utility of infrastructure tags (affixed to walls) for robot localization; in this thesis, we specifically focus on tagging objects. Owing to their low-cost and passive (battery-free) operation, users can apply UHF RFID tags to hundreds of objects throughout their homes. The tags provide two valuable properties for robots: a unique identifier and receive signal strength indicator (RSSI, the strength of a tag's response). This thesis explores robot behaviors and radio frequency perception techniques using robot-mounted UHF RFID readers that enable a robot to efficiently discover, locate, and interact with UHF RFID tags applied to objects and people of interest. The behaviors and algorithms explicitly rely on the robot's mobility and manipulation capabilities to provide multiple opportunistic views of the complex electromagnetic landscape inside a home environment. The electromagnetic properties of RFID tags change when applied to common household objects. Objects can have varied material properties, can be placed in diverse orientations, and be relocated to completely new environments. We present a new class of optimization-based techniques for RFID sensing that are robust to the variation in tag performance caused by these complexities. We discuss a hybrid global-local search algorithm where a robot employing long-range directional antennas searches for tagged objects by maximizing expected RSSI measurements; that is, the robot attempts to position itself (1) near a desired tagged object and (2) oriented towards it. The robot first performs a sparse, global RFID search to locate a pose in the neighborhood of the tagged object, followed by a series of local search behaviors (bearing estimation and RFID servoing) to refine the robot's state within the local basin of attraction. We report on RFID search experiments performed in Georgia Tech's Aware Home (a real home). Our optimization-based approach yields superior performance compared to state of the art tag localization algorithms, does not require RF sensor models, is easy to implement, and generalizes to other short-range RFID sensor systems embedded in a robot's end effector. We demonstrate proof of concept applications, such as medication delivery and multi-sensor fusion, using these techniques. Through our experimental results, we show that UHF RFID is a complementary sensing modality that can assist robots in unstructured human environments.PhDCommittee Chair: Kemp, Charles C.; Committee Member: Abowd, Gregory; Committee Member: Howard, Ayanna; Committee Member: Ingram, Mary Ann; Committee Member: Reynolds, Matt; Committee Member: Tentzeris, Emmanoui

A List of Household Objects for Robotic Retrieval Prioritized by People with ALS (Version 092008)

This technical report is designed to serve as a citable reference for the original prioritized object list that the Healthcare Robotics Lab at Georgia Tech released on its website in September of 2008. It is also expected to serve as the primary citable reference for the research associated with this list until the publication of a detailed, peer-reviewed paper. The original prioritized list of object classes resulted from a needs assessment involving 8 motor-impaired patients with amyotrophic lateral sclerosis (ALS) and targeted, in-person interviews of 15 motor-impaired ALS patients. All of these participants were drawn from the Emory ALS Center. The prioritized object list consists of 43 object classes ranked by how important the participants considered each class to be for retrieval by an assistive robot. We intend for this list to be used by researchers to inform the design and benchmarking of robotic systems, especially research related to autonomous mobile manipulation

Low-cost inertial measurement unit.

Sandia National Laboratories performs many expensive tests using inertial measurement units (IMUs)--systems that use accelerometers, gyroscopes, and other sensors to measure flight dynamics in three dimensions. For the purpose of this report, the metrics used to evaluate an IMU are cost, size, performance, resolution, upgradeability and testing. The cost of a precision IMU is very high and can cost hundreds of thousands of dollars. Thus the goals and results of this project are as follows: (1) Examine the data flow in an IMU and determine a generic IMU design. (2) Discuss a high cost IMU implementation and its theoretically achievable results. (3) Discuss design modifications that would save money for suited applications. (4) Design and implement a low cost IMU and discuss its theoretically achievable results. (5) Test the low cost IMU and compare theoretical results with empirical results. (6) Construct a more streamlined printed circuit board design reducing noise, increasing capabilities, and constructing a self-contained unit. Using these results, we can compare a high cost IMU versus a low cost IMU using the metrics from above. Further, we can examine and suggest situations where a low cost IMU could be used instead of a high cost IMU for saving cost, size, or both

Finding and Navigating to Household Objects with UHF RFID Tags by Optimizing RF Signal Strength

©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 14-18 September 2014, Chicago, IL.DOI: 10.1109/IROS.2014.6942914We address the challenge of finding and navigating to an object with an attached ultra-high frequency radio- frequency identification (UHF RFID) tag. With current off-the- shelf technology, one can affix inexpensive self-adhesive UHF RFID tags to hundreds of objects, thereby enabling a robot to sense the RF signal strength it receives from each uniquely identified object. The received signal strength indicator (RSSI) associated with a tagged object varies widely and depends on many factors, including the object’s pose, material prop- erties and surroundings. This complexity creates challenges for methods that attempt to explicitly estimate the object’s pose. We present an alternative approach that formulates finding and navigating to a tagged object as an optimization problem where the robot must find a pose of a directional antenna that maximizes the RSSI associated with the target tag. We then present three autonomous robot behaviors that together perform this optimization by combining global and local search. The first behavior uses sparse sampling of RSSI across the entire environment to move the robot to a location near the tag; the second samples RSSI over orientation to point the robot toward the tag; and the third samples RSSI from two antennas pointing in different directions to enable the robot to approach the tag. We justify our formulation using the radar equation and associated literature. We also demonstrate that it has good performance in practice via tests with a PR2 robot from Willow Garage in a house with a variety of tagged household objects

A New Vision for Smart Objects and the Internet of Things: Mobile Robots and Long-Range UHF RFID Sensor Tags

Abstract-We present a new vision for smart objects and the Internet of Things wherein mobile robots interact with wirelessly-powered, long-range, ultra-high frequency radio frequency identification (UHF RFID) tags outfitted with sensing capabilities. We explore the technology innovations driving this vision by examining recently-commercialized sensor tags that could be affixed-to or embedded-in objects or the environment to yield true embodied intelligence. Using a pair of autonomous mobile robots outfitted with UHF RFID readers, we explore several potential applications where mobile robots interact with sensor tags to perform tasks such as: soil moisture sensing, remote crop monitoring, infrastructure monitoring, water quality monitoring, and remote sensor deployment

RFID-Guided Robots for Pervasive Automation

©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.DOI: 10.1109/MPRV.2010.17Passive UHF RFID tags are well matched to robots' needs. Unlike lowfrequency (LF) and high-frequency (HF) RFID tags, passive UHF RFID tags are readable from across a room, enabling a mobile robot to efficiently discover and locate them. Using tags' unique IDs, a semantic database, and RF perception via actuated antennas, this paper shows how a robot can reliably interact with people and manipulate labeled objects

Human-Robot Interaction Studies for Autonomous Mobile Manipulation for the Motor Impaired

©2009, Association for the Advancement of Artificial Intelligence (www.aaai.org). The original publication is available at : http://www.aaai.org/Papers/Symposia/Spring/2009/SS-09-03/SS09-03-003.pdf.Presented at Experimental Design for Real-World Systems, AAAI Spring Symposium, March 23-25, 2009 at Stanford University, Stanford, California USA.We are developing an autonomous mobile assistive robot named El-E to help individuals with severe motor impairments by performing various object manipulation tasks such as fetching, transporting, placing, and delivering. El-E can autonomously approach a location specified by the user through an interface such as a standard laser pointer and pick up a nearby object. The initial target user population of the robot is individuals suffering from amyotrophic lateral sclerosis (ALS). ALS, also known as Lou Gehrig’s disease, is a progressive neuro-degenerative disease resulting in motor impairments throughout the entire body. Due to the severity and progressive nature of ALS, the results from developing robotic technologies to assist ALS patients could be applied to wider motor impaired populations. To accomplish successful development and real world application of assistive robot technology, we have to acquire familiarity with the needs and everyday living conditions of these individuals. We also believe the participation of prospective users throughout the design and development process is essential in improving the usability and accessibility of the robot for the target user population. To assess the needs of prospective users and to evaluate the technology being developed, we applied various methodologies of human studies including interviewing, photographing, and conducting controlled experiments. We present an overview of research from the Healthcare Robotics Lab related to patient needs assessment and human experiments with emphasis on the methods of human centered approach

Visual Odometry and Control for an Omnidirectional Mobile Robot with a Downward-Facing Camera

©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.DOI: 10.1109/IROS.2010.5649749Presented at the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 18-22 Oct. 2010, Taipei.An omnidirectional Mecanum base allows for more flexible mobile manipulation. However, slipping of the Mecanum wheels results in poor dead-reckoning estimates from wheel encoders, limiting the accuracy and overall utility of this type of base. We present a system with a downwardfacing camera and light ring to provide robust visual odometry estimates. We mounted the system under the robot which allows it to operate in conditions such as large crowds or low ambient lighting. We demonstrate that the visual odometry estimates are sufficient to generate closed-loop PID (Proportional Integral Derivative) and LQR (Linear Quadratic Regulator) controllers for motion control in three different scenarios: waypoint tracking, small disturbance rejection, and sideways motion. We report quantitative measurements that demonstrate superior control performance when using visual odometry compared to wheel encoders. Finally, we show that this system provides highfidelity odometry estimates and is able to compensate for wheel slip on a four-wheeled omnidirectional mobile robot base

Mg2+ affects the binding of ADP but not ATP to 3-phosphoglycerate kinase. Correlation between equilibrium dialysis binding and enzyme kinetic data.

The role of Mg2+ in the binding of ADP and ATP to pig muscle and yeast 3-phosphoglycerate kinases has been studied by equilibrium dialysis. Whereas the Kd of ATP binding varies between 0.17 and 0.23 mM (S.E.M. 0.03 mM) for both enzymes, independently of the presence of Mg2+, the Kd values for ADP and MgADP binding are in the range 0.18-0.27 mM (S.E.M. 0.04 mM) and 0.05-0.06 mM (S.E.M. 0.01 mM) respectively. Thus Mg2+ exclusively tightens the interaction of ADP, but not of ATP, with the protein molecule. Although the equilibrium dialysis data are consistent with a model possessing a single site for nucleotides, the existence of a much weaker secondary site (with a Kd value at least two orders of magnitude larger) cannot be excluded. The binding of AMP and adenosine to pig muscle 3-phosphoglycerate kinase is weaker than binding of MgATP; the respective Kd values are 0.36 +/- 0.05 mM and 0.65 +/- 0.05 mM. Thus, in addition to the interaction of the alpha-phosphate that is detectable by crystallography [Banks, Blake, Evans, Haser, Rice, Hardy, Merrett and Phillips (1979) Nature (London) 279, 773-777], the beta- and/or gamma-phosphate(s) of MgATP may also interact with the enzyme molecule. The fact that MgADP binds more tightly than ADP is consistent with its stronger inhibition of the reaction catalysed by the enzyme between 3-phosphoglycerate and MgATP. MgADP is a product of this reaction, and inhibits it competitively with both substrates; as an inhibitor its KI is comparable with the Kd found in binding studies. At the same time, the Km value for MgADP in the reverse reaction (0.18 +/- 0.05 mM; mean +/- S.E.M.) is higher than these constants; this may be due either to a different kinetic mechanism in this direction of the enzymic reaction, or to different binding modes of MgADP as inhibitor and as substrate. The reason why inhibition by MgADP is competitive with 3-phosphoglycerate may be that its binding prevents the specific change in conformation that the enzyme undergoes [Harlos, Vas and Blake (1992) Proteins 12, 133-144] when it binds 3-phosphoglycerate