text: 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.
  @cite_18: 
  @cite_4: Robot search and rescue is a time critical task, i.e. a large terrain has to be explored by multiple robots within a short amount of time. The efficiency of exploration depends mainly on the coordination between the robots and hence on the reliability of communication, which considerably suffers under the hostile conditions encountered after a disaster. Furthermore, rescue robots have to generate a map of the environment which has to be sufficiently accurate for reporting the locations of victims to human task forces. Basically, the robots have to solve autonomously in real-time the problem of Simultaneous Localization and Mapping (SLAM). This paper proposes a novel method for real-time exploration and SLAM based on RFID tags that are autonomously distributed in the environment. We utilized the algorithm of Lu and Milios [7] for calculating globally consistent maps from detected RFID tags. Furthermore we show how RFID tags can be used for coordinating the exploration of multiple robots. Results from experiments conducted in the simulation and on a robot show that our approach allows the computationally efficient construction of a map within harsh environments, and coordinated exploration of a team of robots.
  @cite_8: We address the challenge of finding and navigating to an object with an attached ultra-high frequency radiofrequency identification (UHF RFID) tag. With current off-theshelf 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 properties 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.
  @cite_1: With the emerging mass production of very small, cheap Radio Frequency Identification (RFID) tags, it is becoming feasible to deploy such tags on a large scale. In this paper, we advocate distribution schemes where passive RFID tags are deployed in vast quantities and in a highly redundant fashion over large areas or object surfaces. We show that such an approach opens up a whole spectrum of possibilities for creating novel RFID-based services and applications, including a new means of cooperation between mobile physical entities. We also discuss a number of challenges related to this approach, such as the density and structure of tag distributions, and tag typing and clustering. Finally, we outline two prototypical applications (a smart autonomous vacuum cleaner and a collaborative map-making system) and indicate future directions of research.
  @cite_3: Localization of indoor environment is a fundamental issue for mobile robot. In this paper, we proposed the localization scheme to fusion the RFID localization system, ultrasonic sensor and wheel encoder. The uncertainty is factor caused by each localization system, and the estimation error is affected by this uncertainty. The sensor system for mobile robot localization is technical limitation such as sensing range, operation feature. Therefore we focus on sensor fusion scheme. When the mobile robot moves, certain data combination set to fuse is selected according to the environmental factor. The performance and simplicity of the approach is demonstrated with the result produced by experiments using mobile robot.
  @cite_23: Successful management of medications is critical to maintaining healthy and independent living for older adults. However, medication non-adherence is a common problem with a high risk for severe consequences [5], which can jeopardize older adults' chances to age in place [1]. Well-designed robots assisting with medication management tasks could support older adults' independence. Design of successful robots will be enhanced through understanding concerns, attitudes, and preferences for medication assistance tasks. We assessed older adults' reactions to medication hand-off from a mobile manipulator with 12 participants (68-79 years). We identified factors that affected their attitudes toward a mobile manipulator for supporting general medication management tasks in the home. The older adults were open to robot assistance; however, their preferences varied depending on the nature of the medication management task. For instance, they preferred a robot (over a human) to remind them to take medications, but preferred human assistance for deciding what medication to take and for administering the medication. Factors such as perceptions of one's own capability and robot reliability ifluenced their attitudes.
  @cite_2: Presented at IROS 2009 workshop: Semantic Perception for Mobile Manipulation, 15 October 2009, St. Louis, MO, USA.
  @cite_15: We present a unique multi-antenna RFID reader (a sensor) embedded in a robot's manipulator that is designed to operate with ordinary UHF RFID tags in a short-range, near-field electromagnetic regime. Using specially designed near-field antennas enables our sensor to obtain spatial information from tags at ranges of less than 1 meter. In this work, we characterize the near-field sensor's ability to detect tagged objects in the robots manipulator, present robot behaviors to determine the identity of a grasped object, and investigate how additional RF signal properties can be used for “pre-touch” capabilities such as servoing to grasp an object. The future combination of long-range (far-field) and short-range (near-field) UHF RFID sensing has the potential to enable roboticists to jump-start applications by obviating or supplementing false-positive-prone visual object recognition. These techniques may be especially useful in the healthcare and service sectors, where mis-identification of an object (for example, a medication bottle) could have catastrophic consequences.
  @cite_20: In recent years, there has been an increasing interest within the robotics community in investigating whether Radio Frequency Identification (RFID) technology can be utilized to solve localization and mapping problems in the context of mobile robots. We present a novel sensor model which can be utilized for localizing RFID tags and for tracking a mobile agent moving through an RFID-equipped environment. The proposed probabilistic sensor model characterizes the received signal strength indication (RSSI) information as well as the tag detection events to achieve a higher modeling accuracy compared to state-of-the-art models which deal with one of these aspects only. We furthermore propose a method that is able to bootstrap such a sensor model in a fully unsupervised fashion. Real-world experiments demonstrate the effectiveness of our approach also in comparison to existing techniques.
  @cite_11: Our goal is to develop intelligent service robots that operate in standard human environments, automating common tasks. In pursuit of this goal, we follow the ubiquitous robotics paradigm, in which intelligent perception and control, are combined with ubiquitous computing. By exploiting sensors and effectors in its environment, a robot can perform more complex tasks without becoming overly complex itself. Following this insight, we have developed a service robot that operates autonomously in a sensor-equipped kitchen. The robot learns from demonstration, and performs sophisticated tasks, in concert with the network of devices in its environment. We report on the design, implementation, and usage of this system, which is freely available for use, and improvement by others, in the research community.
summary: Roboticists have employed RFID to great effect. The unique identifier has proved useful for object recognition @cite_11 , as a high-confidence landmark in SLAM implementations @cite_4 , for waypoint navigation @cite_1 , and as a complementary sensing modality for multi-sensor fusion @cite_3 . Many of these systems rely on low-frequency (LF) and high-frequency (HF) RFID tags, which have very short read ranges (5-10 @math cm ). In contrast, ultra-high frequency (UHF) tags can be used for both short-range operation @cite_15 as well as long-range operation out to several meters @cite_18 . In robotics, UHF RFID tags have been used for robot localization @cite_20 , to locate tagged objects @cite_8 , for medication delivery @cite_23 , and for manipulation @cite_2 .