Cooperative Relative Positioning of Mobile Users by Fusing IMU Inertial and UWB Ranging Information

Relative positioning between multiple mobile users is essential for many applications, such as search and rescue in disaster areas or human social interaction. Inertial-measurement unit (IMU) is promising to determine the change of position over short periods of time, but it is very sensitive to error accumulation over long term run. By equipping the mobile users with ranging unit, e.g. ultra-wideband (UWB), it is possible to achieve accurate relative positioning by trilateration-based approaches. As compared to vision or laser-based sensors, the UWB does not need to be with in line-of-sight and provides accurate distance estimation. However, UWB does not provide any bearing information and the communication range is limited, thus UWB alone cannot determine the user location without any ambiguity. In this paper, we propose an approach to combine IMU inertial and UWB ranging measurement for relative positioning between multiple mobile users without the knowledge of the infrastructure. We incorporate the UWB and the IMU measurement into a probabilistic-based framework, which allows to cooperatively position a group of mobile users and recover from positioning failures. We have conducted extensive experiments to demonstrate the benefits of incorporating IMU inertial and UWB ranging measurements.Comment: accepted by ICRA 201

DESIGN & DEVELOPMENT OF A 2-DOF MINIATURE FORCE SENSOR FOR SURGICAL PROCEDURES

ABSTRACT Force sensing is an important component for a number of surgical procedures as it can help to prevent undesirable damage to the tissue and at the same time provides the surgeons with a better "feel" of the tool-tissue interaction. However, most of the current commercially available multi-DOF force sensors are relatively large in size and it is a challenge to incorporate them into the surgical tool. Hence, a multi-DOF miniature force sensor is desired and this paper presents the design and development of a miniature 2-DOF force sensor. In order to achieve a miniature force sensor, microfabrication technique is used and the proposed force sensor is a capacitive-based sensor. The proposed force sensor can be used in a number of percutaneous procedures as well as catheter-based procedures. This paper presents the design and microfabrication process of the proposed miniature force sensor

Designettes: An Approach to Multidisciplinary Engineering Design Education

Design and other fundamental topics in engineering are often isolated to dedicated courses. An opportunity exists to foster a culture of engineering design and multidisciplinary problem solving throughout the curriculum. Designettes, charettelike design challenges, are rapid and creative learning tools that enable educators to integrate design learning in a single class, across courses, across terms, and across disciplines. When two or more courses join together in a designette, a multidisciplinary learning activity occurs; multiple subjects are integrated and applied to open-ended problems and grand challenges. This practice helps foster a culture of design, and enables the introduction of multidisciplinary design challenges. Studies at the Singapore University of Technology and Design (SUTD) demonstrate learning of engineering subject matter in a bio-inspired robotics designette (MechAnimal), an interactive musical circuit designette, and an automated milk delivery (AutoMilk) designette. Each challenge combines problem clarification, concept generation, and prototyping with subject content such as circuits, biology, thermodynamics, differential equations, or software with controls. From pre- and postsurveys of students, designettes are found to increase students' understanding of engineering concepts. From 321 third-semester students, designettes were found to increase students' perceptions of their ability to solve multidisciplinary problems

Multi-AGV's Temporal Memory-based RRT Exploration in Unknown Environment

With the increasing need for multi-robot for exploring the unknown region in a challenging environment, efficient collaborative exploration strategies are needed for achieving such feat. A frontier-based Rapidly-Exploring Random Tree (RRT) exploration can be deployed to explore an unknown environment. However, its' greedy behavior causes multiple robots to explore the region with the highest revenue, which leads to massive overlapping in exploration process. To address this issue, we present a temporal memory-based RRT (TM-RRT) exploration strategy for multi-robot to perform robust exploration in an unknown environment. It computes adaptive duration for each frontier assigned and calculates the frontier's revenue based on the relative position of each robot. In addition, each robot is equipped with a memory consisting of frontier assigned and share among fleets to prevent repeating assignment of same frontier. Through both simulation and actual deployment, we have shown the robustness of TM-RRT exploration strategy by completing the exploration in a 25.0m x 54.0m (1350.0m2) area, while the conventional RRT exploration strategy falls short.Comment: 8 pages, 10 Figure

Exploiting Radio Fingerprints for Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is paramount for unmanned systems to achieve self-localization and navigation. It is challenging to perform SLAM in large environments, due to sensor limitations, complexity of the environment, and computational resources. We propose a novel approach for localization and mapping of autonomous vehicles using radio fingerprints, for example WiFi (Wireless Fidelity) or LTE (Long Term Evolution) radio features, which are widely available in the existing infrastructure. In particular, we present two solutions to exploit the radio fingerprints for SLAM. In the first solution-namely Radio SLAM, the output is a radio fingerprint map generated using SLAM technique. In the second solution-namely Radio+LiDAR SLAM, we use radio fingerprint to assist conventional LiDAR-based SLAM to improve accuracy and speed, while generating the occupancy map. We demonstrate the effectiveness of our system in three different environments, namely outdoor, indoor building, and semi-indoor environment.Comment: This paper has been accepted by IEEE Pervasive Computing with DOI: 10.1109/MPRV.2023.327477