While tactile sensing is widely accepted as an important and useful sensing modality, its use pales in comparison to other sensory modalities like vision and proprioception. AnySkin addresses the critical challenges that impede the use of tactile sensing - versatility, replaceability, and data reusability. Building on the simplistic design of ReSkin, and decoupling the sensing electronics from the sensing interface, AnySkin simplifies integration making it as straightforward as putting on a phone case and connecting a charger. Furthermore, AnySkin is the first uncalibrated tactile-sensor to report crossinstance generalizability of learned manipulation policies. To summarize, this work makes three key contributions: first, we introduce a streamlined fabrication process and a design tool for creating an adhesive-free, durable and easily replaceable magnetic tactile sensor; second, we characterize slip detection and policy learning with the AnySkin sensor; third, we demonstrate zero-shot generalization of models trained on one instance of AnySkin to new instances, and compare it with popular existing tactile solutions like DIGIT and ReSkin. Code, design files, and videos of policy experiments can be found on https://any-skin.github.io

Recording 3D movements of a user's hand, robotic arms, or an object, even in a small confined space, has several applications in AR/VR, robotics, movement science, and 3D modeling and rendering. Existing camera-based tracking systems, though extremely accurate, are quite expensive and suffer from issues of occlusion and face difficulties when operating in extremely dark or extremely bright environments. We contend that trading-off a bit of accuracy while reducing costs and enabling more flexible operating environment might be worth exploring. This paper presents UTrack3D, a table-top setup that tracks the movements of an object in 3D space using embedded low-cost ultra-wideband (UWB) radios. The core idea is to continuously track the changes in phase as captured from UWB signal's channel impulse response (CIR) derived from the UWB messages received at a set of dual-antenna UWB receivers. Each of our custom dual-antenna receivers captures the UWB signal from two corners of a cuboid allowing us to perform relative phase measurements. The main challenges in the solution are caused by a location-dependant large variation in the signal amplitudes and corruption of the CIR due to multipath. UTrack3D tackles these challenges via a signal processing pipeline fusing a forward localization process which tracks the object's location using UWB CIR phase, and a posterior location check process, which validates the estimated location. UTrack3D is implemented on commercial-off-the-shelf (COTS) UWB chips, and provides a 90th percentile accuracy of 9 mm in a table-top 3D region (1.5m × 0.8m × 0.8m). We evaluate the effects of additional UWB receivers, effect of different movement speeds, and effect of small-scale signal blocking using different materials. We expect UTrack3D to allow researchers a rich new environment for further advancing UWB-based 3D tracking.

This paper presents an ultra-wideband (UWB) based two-factor authentication (2FA) platform, called UWB-Auth, designed as carriable or wearable devices. UWB-Auth eliminates various social engineering attacks, including phishing attack, 2FA-fatigue attack, co-located attack etc., on existing 2FA solutions like Duo and reveals simple and fast user interaction. The key innovation of UWB-Auth is a novel combination of location authentication via UWB, checking whether a legitimate token is in the vicinity of the login device with centimeter-level accuracy, followed by an abstraction layer allowing different knowledge-based or biometric-based authentication, ensuring the user's identity and intent to login. Moreover, UWB-Auth reverses the sequence in which the two factors are verified, providing robust defences against data breach. We develop 3 UWB-Auth prototypes: a key-chain token, a smartwatch with commercial knowledge/biometric factor, and a smartring with customized knowledge/biometric authentication algorithm to demonstrate the effectiveness of UWB-Auth. Overall, UWB-Auth completes the whole authentication process in 4 seconds, and completely rejects malicious requests when the token is 20cm or 10^\circ outside a small valid physical area near the login device. Even when a malicious entity gains physical access to the token, UWB-Auth stops attack attempts via knowledge and biometric authentication.

Low-power wide-area networks (LPWAN) evolve rapidly with advanced communication primitives (e.g., coding, modulation) being continuously invented. This rapid iteration on LPWAN, however, forms a communication barrier between legacy wireless sensor nodes deployed years ago (e.g., ZigBee-based sensor node) with their latest competitor running a different communication protocol (e.g., LoRa-based IoT node): they work on the same frequency band but share different MAC- and PHY-layer regulations and thus cannot talk to each other directly. To break this barrier, we propose LigBee, a cross-technology communication (CTC) solution that enables symbol-level communication from the latest LPWAN LoRa node to legacy ZIGBEE node. We have implemented LigBee on both software-defined radios and commercial-off-the-shelf (COTS) LoRa and ZigBee nodes, and demonstrated that LigBee builds a reliable CTC link from LoRa node to ZigBee node on both platforms. Our experimental results show that i) LigBee achieves a bit error rate (BER) in the order of 10−3with 70 ∼ 80% frame reception ratio (FRR), ii) the range of LigBee link is over 300m, which is 6 ∼ 7.5× the typical range of legacy ZigBee and state-of-the-art solution, and iii) the throughput of LigBee link is maintained on the order of kbps, which is close to the LoRa’s throughput.

High-precision tracking of a pen-like instrument's movements is desirable in a wide range of fields spanning education, robotics, and art, to name a few. The key challenge in doing so stems from the impracticality of embedding electronics in the tip of such instruments (a pen, marker, scalpel, etc.) as well as the difficulties in instrumenting the surface that it works on. In this paper, we present ITrackU, a movement digitization system that does not require modifications to the surface or the tracked instrument's tip. ITrackU fuses locations obtained using ultra-wideband radios (UWB), with an inertial and magnetic unit (IMU) and a pressure sensor, yielding multidimensional improvements in accuracy, range, cost, and robustness, over existing works. ITrackU embeds a micro-transmitter at the base of a pen which creates a trackable beacon, that is localized from the corners of a writing surface. Fused with inertial motion sensor and a pressure sensor, ITrackU enables accurate tracking. Our prototype of ITrackU covers a large 2.5m × 2m area, while obtaining around 2.9mm median error. We demonstrate the accuracy of our system by drawing numerous shapes and characters on a whiteboard, and compare them against a touchscreen and a camera-based ground-truthing system. Finally, the produced stream of digitized data is minuscule in volume, when compared with a video of the whiteboard, which saves both network bandwidth and storage space.

The coronavirus pandemic is altering our way of life. As more establishments open, there is an expectation that people will follow physical distancing guidelines. The implementation, however, is poor; just putting up warning signs appealing the general public to keep a distance of 6 feet from others is hardly enough. In this paper we consider the design of a wearable device that raises an alarm if another similar device is detected within a set distance. It uses off-the-shelf ultra-wideband radio technology for real-time, accurate distance estimation from others in the vicinity. We design an one-to-all ranging protocol that is able to accurately estimate distance to neighboring devices and warn the user if the distance falls below a certain established threshold within a short time. The device must compensate for human occlusions and avoid unnecessary warnings when physical barriers exist between devices. We implement and evaluate our protocol in a small testbed with custom prototype hardware as well as in simulation. Our ranging protocol is capable of performing up to 10 distance measurements per second, while avoiding packet collisions. The overall percentage of rangings completed is around 65% in a 10-node network, and the distance accuracy is around 20cm even with frequent human occlusions. We believe this prototype will provide the first steps to ensure physical distancing in various real-world settings.

Unmanned Aerial Vehicles (UAVs) are quickly becoming a viable delivery platform for physical packages with promise to transform the retail industry's supply chains. This work focuses on the last leg of such delivery: physically approaching a customer's landing zone. This has traditionally relied on a combination of GPS and computer-vision to locate and identify a landing zone. Instead of using computer vision, we propose to use ultra-wideband beacons (UWB) to assist in the landing process. The UAV's location relative to the landing zone is continuously measured based on the wireless propagation delay between the UAV and the landing zone's corners. We show that a single pair of wireless devices, one at the UAV and one at the landing zone, suffices to obtain the UAV's location. The landing zone's UWB device, connected to multiple antennas, receives multiple copies of the UAV's signals, that enables a sub-decimeter 3D-localization of the UAV. This helps the UAV's control logic governing the approach and landing process.

The number of Internet of Things is growing exponentially, among which the ZigBee devices are being widely deployed, incurring severe collision problem in ZigBee networks. Instead of collision avoidance or packet retransmissions which introduce extra time/energy overhead, existing methods try to decompose multi-packet collision directly. For example, state-of-the-art mZig exploits collision-free chips to decompose the collided chips iteratively, however, suffers from the high bit error rate and low frame reception rate which limit the practical applications. Toward this end, we observe three major issues of existing solutions: 1) all existing solutions adopt the priori-chip-dependent decomposition pattern, leading to the error propagation; 2) the available samples for chip decoding can be scarce, resulting in severe scarce-sample errors; 3) existing solutions assume the consistent frequency offset for consecutive packets, leading to inaccurate frequency offset estimation. To solve these issues in collision decomposition, we propose FORWARD, a novel physical layer design to enable accurate collision decoding in ZigBee. The key idea is to generate all possible overlapping combinations as reference waveforms. The decomposition is determined by comparing the collided signal with the reference waveforms. Such a priori-chip-independent design has the advantages to eliminate the error propagation. To ensure sufficient samples for decoding, FORWARD always choose the longest segment as reference. Furthermore, the real-time channel estimation and frequency offset calibration ensure the accurate collision decoding. We implement FORWARD on USRP platform and evaluate its performance. Experimental results demonstrate that FORWARD reduces bit error rate by order of magnitude and increases frame reception rate by 10% ~ 50% compared with the state-of-the-art.

As wireless communication is tailored for low-power devices while the number of Internet of Things is growing exponentially, the collision problem in ZigBee is worsen. The classical approaches of solving collision problems lie in collision avoidance and packet retransmission, which could incur considerable overhead. The new trend is to decompose multipacket collision directly, however, the high bit error rate limits its practical applications. Toward this end, we observe three major issues in the existing solutions: 1) all existing solutions adopt the priori-chip-dependent decomposition pattern, leading to the error propagation; 2) the available samples for chip decoding can be scarce, resulting in severe scarce-sample errors; 3) existing solutions assume the consistent frequency offset for consecutive packets, leading to inaccurate frequency offset estimation. To solve the issues of collision decomposition in ZigBee, we propose FORWARD, a novel physical layer design to enable highly accurate collision decomposition in ZigBee. The key idea is to generate all possible collided combinations as reference waveforms. The decomposition is determined by comparing the collided signal with the reference waveforms. Such a priori-chip-independent design has the advantages to eliminate the cumulative errors incurred from error propagation. When decoding, FORWARD always choose the longest segment to ensure sufficient samples for decoding. Furthermore, the recursive calibration design is approaching the real-time frequency offset and dynamically compensates the reference waveform. We implement FORWARD on USRP based testbed and evaluate its performance. Experimental results demonstrate that FORWARD reduces bit error rate by 4.96× and increases throughput 1.46~2.8× compared with the state-of-the-art mZig.

With the proliferation of IoTs, massive deployments of ZigBee devices intensify the collision, a fundamental problem in wireless communication. Conventional solutions exploit the protocol based on CSMA to avoid collision, which incurs considerable overhead. Recently, new solutions which focus on concurrent transmission via collision decomposition are proposed instead of collision avoidance. However, existing approaches to collision decomposition in ZigBee suffer the problems of error propagation and scarce-sample error. To make up the weakness of existing solutions, we propose a novel solution, reZig, which leverages the generated reference waveform in the receiver to infer each single waveform in the collision. By inferring the chip independently, reZig is error-propagation-free. As there are multiple segments provided to decode one chip, reZig can select the segment with most raw samples to ensure the decoding reliability. We implement reZig on the USRP N210 testbed. Experiments demonstrate that reZig achieves the 1.46~ 2.8× throughput compared to mZig, the state-of-the-art collision-decomposition approach to ZigBee.

ZigBee is a widely used wireless technology in low-power and short-range scenarios such as the Internet of Things, sensor networks, and industrial wireless networks. However, the traditional ZigBee supports only one data rate, 250 Kbps, which thoroughly limits ZigBee's efficiency in dynamic wireless channels. In this paper, we propose Mrs. Z, a novel physical layer design to enable multi-rate selection in ZigBee with lightweight modification on the legacy ZigBee modules. The key idea is to change the single spectrum spreading length to multiple ones. Correspondingly, to support the rate adaptation to the channel variations, we propose a bit-error-based rate selection scheme, which predicts BER by leveraging the physical properties of ZigBee to calculate the confidence for each symbol in transmission. Then, the receiver selects the rate based on the negative impact on throughput incurred by bit errors and gives feedback to the transceiver. We implement Mrs. Z on USRPs and evaluate its performance in different scenarios. Experiment results demonstrate that Mrs. Z achieves about 1.15, 1.2, and 1.8 × average throughput compared to the classic smart pilot, softrate, and the traditional ZigBee.

Smart devices (e.g., smartphones or tablets) have become an indispensable part of our daily lives for conducting mobile payment transactions, and storing both corporate and personal sensitive data. As a result, unauthorized access to smart devices can result in a catastrophic security breach. Lock screen provides the first line of defense against unauthorized access to smart devices, where users typically use the PIN, the pattern of drawing, or biometric to unlock their devices. Unfortunately, recent studies have revealed that individual unlocking methods are insufficient to prevent unauthorized access to smart devices. In this paper, we aim to increase the security barrier of smart device unlocking. We present the CP3, a combined unlocking framework to achieve highly secure and usable authentication for commodity smart devices. We address several challenges of combing unlocking methods from different modalities, such as the high reliability and low latency. We implement a prototype of our approach based on the Android platform, which selects the fingerPrint authentication, bluetooth transmission Power authentication and facial Pattern verification as our typical Combination for the secure unlocking. We have made the source code of our implementation public. Real-world experiments demonstrate the effectiveness of our solution. CP3achieves 88 % accuracy and 2.88s operation latency, which guarantees both good user experience and high security level compared with existing methods.

ZigBee is a widely used wireless technology in low-power and short-range scenarios such as Internet of Things (IoT), sensor networks, and industrial wireless networks. However, the standard ZigBee supports only one data rate, 250Kbps, which thoroughly limits ZigBee's efficiency in dynamic wireless channels. In this paper, we propose Mrs.Z, a novel physical layer design to enable multi-rate selection in ZigBee. The key idea is to change the single spectrum spreading length to multiple ones. Correspondingly, to gracefully adapt to the channel variations, we propose a BER-based rate selection scheme, dividing bit errors into two categories: errors caused by the exceeding despreading threshold, which can be discovered in the physical layer, and caused by incorrect despreading, which is not visible until cyclic redundancy check (CRC) in the media access control (MAC) layer. Then, the receiver selects the rate based on the underlying negative impacts incurred by them and feedbacks to the transceiver. We implement Mrs.Z on USRPs and evaluate its performance in different scenarios. Results demonstrate that Mrs.Z achieves an improvement of 20% and 80% compared to the classic SoftRate and the standard ZigBee.

A well-designed energy-efficient routing protocol is an indispensable part for prolonging the lifetime of wireless sensor networks (WSNs) because a sensor node usually has limited energy. Many research efforts are contributed on routing design in WSNs. With the development of green technology, the energy harvesting technique is being applied to real WSNs. Therefore, existing routing protocols are not suitable for such new WSNs with energy harvesting. In this paper, we concentrate on designing a novel routing protocol, named energy harvesting routing (EHR), which takes energy harvesting as one major factor into routing design to improve the energy efficiency. First, we introduce a hybrid routing metric combining the effect of residual energy and energy harvesting rate. Then we propose an updating mechanism allowing every node to maintain dynamic energy information of its neighbors. Based on the hybrid metric and the neighbor information, EHR is able to locally select the optimal next hop. Extensive simulations are conducted to evaluate the performance of EHR. Results demonstrate that EHR outperforms existing routing protocols in energy harvesting WSNs in term of the energy efficiency.