L. Girod and D. Estrin, "Robust Range Estimation Using Acoustic and Multimodal Sensing," Proc. IEEE/RSJ Int'l Conf. Intelligent Robots and Systems (IROS 2001.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....radio for measuring the range between nodes, for example, by observing the signal strength. Experience has shown, however, that this approach yields poor distance estimates [14] Much better results are obtained by timeof flight measurements, particularly when acoustic and RF signals are combined [12,15]; accuracies of a few percent of the transmission range are reported. Our simulation results provide insight into the e#ect of the accuracy of the distance measurements on the localization algorithms. It is important to realize that the main three context parameters (connectivity, anchor ....

L. Girod, D. Estrin, Robust range estimation using acoustic and multimodal sensing, in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Maui, Hawaii, 2001.

....wireless footprints which can then be coupled to the CP and AP models. Routing strategies need to be specifically tailored to the underlying network building algorithm. Our adaptive power algorithm would require that the devices have either directional antennae or other means of directional sensing[22]. Design issues for such systems need to be considered. Ad hoc networks also provide us with opportunities for intelligent noise cancellation schemes, which have yet to be introduced and studied. Furthermore, actual ad hoc networks will experience noise and scattering from the environment which ....

L. Girod and D. Estrin, "Robust range estimation using acoustic and multimodal sensing," in Proceedings of the IEEE/RSJ Intl Conf on Intelligent Robots and Systems (IROS), 2001.

....to the distance estimation. Such RF systems [8] 44] run into problems as multi path fading, background interference, and irregular signal propagation characteristics, shown in empirical study [33] make range estimates inaccurate. Work to mitigate such error such as robust range estimation in [34], Two phase refinement positioning [85] 87] and parameter calibration in [100] have been proposed that take advantage of averaging, smoothing, and alternate hybrid techniques to reduce error to within some acceptable limit. Given the inherent constrains of the sensor devices envisioned and ....

L. Girod and D. Estrin, "Robust Range Estimation using Acoustic and Multimodal Sensing", In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS `01), Maui, Hawaii, October 2001.

....estimates. For RF systems [1] 14] problems occur as multi path fading, background interference, and irregular signal propagation characteristics (shown in an empirical study of this technology [10] make range estimates inaccurate. Work to mitigate such errors such as robust range estimation ([11]) two phase refinement positioning ( 28] 30] and parameter calibration ( 33] have been proposed to take advantage of averaging, smoothing, and alternate hybrid techniques to reduce error to within some acceptable limit. While solutions based on RSSI have demonstrated efficacy in simulation ....

L. Girod and D. Estrin, Robust Range Estimation using Acoustic and Multimodal Sensing, In Proceedings of IROS 01, Maui, Hawaii, October 2001.

.... widely used as a ready to use, well supported solution when size constraints are given and systems with more than two or three laptops are desirable [9, 10, 11] Recently, commercially available motes have been used in conjunction with PDA s to be able to increase the number of available nodes [12, 13, 14]. The great success of the motes and of TinyOS as a prototyping platform shows, that a demand for such systems is clearly available and further research necessary. Other prototyping systems are based on FPGAs, StrongARM processors etc. 15, 4] The Pushpin nodes developed by the MIT Amorphous ....

L. Girod and D. Estrin, "Robust range estimation using acoustic and multimodal sensing," in Proceedings 2001.

....of different kinds of signals. Typically, the radio signal is used in combination with acoustic, ultrasound or infrared signals. ToAbased techniques provide a much better accuracy than RSSI based mechanisms, and can be implemented at a reasonable cost. For example, the tech nique proposed in [8] uses a standard PC sound card to generate an acoustic signal, which is received by a cheap microphone. The authors show that this technique provides good accuracy (below 3 ) in re alistic conditions. However, accuracy drops to only 23 when the line of sight between the nodes is obstructed by ....

....are reported in logarithmic scale. simulations we set 0.84 and c 2. With these settings, 70 of the estimations are within 10 of the actual distance 5. To model errors in ToA based distance estima tion, we have simplified the scheme of [26] which is based on the acoustic ranging technique of [8]. In this case, the error can be seen as the sum of three independent components: speed of sound error: changes in the atmospheric conditions can generate both a positive and a negative error in the distance reading. We denote this error with qqE. Non Line Of Sight error: this error, which ....

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L. Girod, D. Estrin, "Robust Range Estimation Using Acoustic and Multimodal Sensing", IEEE/RSJ International Conference on Intelligent Robots and Systems, 2001.

....provide location estimates even in the case of an obstructed line of sight. However, the resulting location estimates are typically wrong due to relying on signals reflected around the obstruction. Often it is difficult to detect such situations, which may result in using wrong location estimates [13]. With the Lighthouse location system, on the other hand, nodes will either obtain a good location estimate or none at all. This is due to the fact that diffuse reflection (e.g. at walls) reduces the light intensity of the laser beam so much that the photo detector will not detect the reflected ....

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) 2001.

....cm from the actual positions. It must be mentioned however that ultrasound has a shorter range and lower tolerance for obstacles in the path than radio signals, and is included in the design of a sensor node solely for the purposes of localization. Acousticbased distance measurements are used in [8], where it is reported that the precision of ultrasound is in the sub cm range, when the line of sight is not obstructed, and microphones and speakers are directed at each other. In [8] it is proposed that the ambiguities created from obstructed line of sight can be solved either by employing ....

....design of a sensor node solely for the purposes of localization. Acousticbased distance measurements are used in [8] where it is reported that the precision of ultrasound is in the sub cm range, when the line of sight is not obstructed, and microphones and speakers are directed at each other. In [8], it is proposed that the ambiguities created from obstructed line of sight can be solved either by employing additional sensors, e.g. cameras to detect obstructed line of sight, or using localization algorithms that detect inconsistencies. Once the distances are measured and initial locations ....

[Article contains additional citation context not shown here]

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

....for measuring the range between nodes, for example, by observing the signal strength. Experience has shown, however, that this approach yields very inaccurate distances [8] Much better results are obtained by time of flight measurements, particularly when acoustic and RF signals are combined [6, 12]; accuracies of a few percent of the transmission range are reported. Acoustic signals, however, are temperature dependent and require an unobstructed line of sight. Furthermore, even small errors do accumulate when propagating distance information over multiple hops. A drastic approach that ....

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Maui, Hawaii, October 2001.

....to note that there are other sensors useful for navigation and localization, most notably acoustic and radio based techniques. It is practical (i.e. sensors t the small platform and low power demands) to do sound based time of ight localization and there is active research along these lines [10]. Another method of localization is based on the received signal strength indication (RSSI) of other nearby Robomote radio communications [4] 5] 6] 7] 8] Success along these lines has been mixed and it is not clear whether accurate localization based on radio signal strength is useful ....

....Avg 47 0.16 2028.2 0.16 Std dev 9.2 .03 510.6 0.16 and navigation in general. It is reasonable to hypothesize that working accurate localization in cluttered oce like spaces will require a mixed approach that utilizes the bene ts of many sensor modalities, such as a sound and radio combination [10], 11] In conclusion, when considering the metrics (cost, size, and function) we made Robomote as small as possible while still taking advantage of o the shelf components and keeping a minimum key functionality level. As a result, Robomote is small, cheap, and serves its task. III. Design in ....

D. Estrin L. Girod, \Robust range estimation using acoustic and multimodal sensing," in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2001.

....the RF radio for measuring the range between nodes, for example, by observing the signal strength. Experience has shown, however, that RSSI yields very inaccurate distances [8] Much better results are obtained by time of flight measurements, particularly when acoustic and RF signals are combined [6, 12]; accuracies of a few percent of the transmission range are reported. Acoustic signals, however, are temperature dependent and require an unobstructed line of sight. Furthermore even small errors do accumulate when propagating distance information over multiple hops. A drastic approach that ....

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Maui, Hawaii, Oct. 2001.

....We refer to the nodes that send an estimate of their locations as beacons. Beacons can acquire their location information either from previous multilateration procedures or from other sources such as GPS. Distances can be estimated using either RSSI measurements [Sav01a] ultrasound measurements [Gir01], or a combination of both [Sav01b] To estimate the location of a node we compute the local minimum of the function L 2 , express as: N i i i R y x D y x L 1 0 2 2 ) where D i is the approximate distance between the estimated location of node i and the location ....

L. Girod, D. Estrin, Robust Range Estimation Using Acoustic And Multimodal Sensing. IEEE/RSI Int. Conf. on Intelligent Robots and Systems (IROS

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L. Girod and D. Estrin, Robust range estimation using acoustic and multimodal sensing, in: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, Maui, HI (October 2001).

....performed, that is all sensors are assumed to be absolutely correct. 2.1.2 Assumptions and Limitations Our calibration algorithm assumes that locations of the nodes are known. There has been a lot of work done in the area of robust mechanisms for ne grained rang11 ing and localization, such as [WJH97, GE01, GBE02]. Our algorithm depends on the ability to perform synchronized sampling. Schemes such as RBS [EGE02] have been demonstrated to suit this purpose [BME03] Our relative calibration scheme also requires a priori knowledge of the sensor calibration function. That is, the parametric form of the ....

L. Girod and D. Estrin. \Robust Range Estimation Using Acoustic and Multimodal Sensing." In International Conference on Intelligent Robots and Systems, October 2001. 31

....sensornets with nodes that are spread out over an area whose approximate geographic boundaries are known to the network operators. We assume that nodes know their geographic location. This can be achieved through the use of GPS or some other approximate but less burdensome localization technique [4, 9, 22, 23, 25]. This assumption is critical for our proposed data centric storage algorithm. However, we think it is a reasonable assumption because in many cases the sensornet data are useful only if the location of their source is known. We assume that the sensornet is connected to the outside world through ....

L. Girod and D. Estrin, Robust Range Estimation using Acoustic and Multimodal Sensing, In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, (Maui, Hawaii, October 2001).

....and distortions resulting from fixed elements must be compensated by detecting and adapting to these conditions. An approach aimed at characterizing the environment has the potential to improve sensing fidelity as well as energy efficiency. For example, in the multi modal localization system [GE01b] previously described, nodes could retain long term information about non line of sight pairs detected when obstructions change slowly. Savvides et al. [SHS01a] propose an approach by which nodes in a wireless network can improve the accuracy of their RSSI based location estimates (discussed in ....

....self calibration in sensor nodes. We can potentially leverage their techniques. 6.6 Goals of Self Configuration The goal of self configuration is for beacons to automatically adapt to variations in density, environment and miscalibration. Others have addressed adapting to a fixed environment [SHS01a, GE01b] and to miscalibration [HWB00] 78 Figure 6.5: A self configuring localization system architecture. This dissertation focuses on adapting to beacon density. We have formally introduced the notion of beacon density and shown that the quality of localization can be related to the density of ....

Lewis Girod and Deborah Estrin. "Robust Range Estimation Using Acoustic and Multimodal Sensing." In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2001), volume 3, pp. 1312--1320. IEEE, March 2001.

....node is equipped with 40KHz ultrasonic sensors that have an e#ective range of 5 meters and approximately 1cm accuracy. Similar technologies can produce longer ranges, but we found this range to be more appropriate for indoor settings. The wideband acoustic method presented by Girod and Estrin in [5] is also a notable ranging technology that provides some immunity to common multipath e#ects and would provide a good ranging alternative. Figure 2: Our experimental node 3.3 Solution Outline In this paper the single hop multilateration operation performed by GPS is extended to operate on ....

L. Girod and D. Estrin , Robust range estimation using acoustic and multimodal sensing Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

....sensornets with nodes that are spread out over an area whose approximate geographic boundaries are known to the network operators. We assume that nodes know their geographic location. This can be achieved through the use of GPS or some other approximate but less burdensome localization technique [3, 8, 19, 20, 22]. This assumption is critical for our proposed data centric storage algorithm. However, we think it is a reasonable assumption because in many cases the sensornet data are useful only if the location of their source is known. We assume that the sensornet is connected to the outside world through ....

L. Girod and D. Estrin, Robust range estimation using acoustic and multimodal sensing, In Proceedings of the IEEE Conference on Intelligent Robots and Systems, 2001.

....approximate geographic boundaries are known to network operators. We assume nodes have short range communication, but are within radio range of several other nodes. We further assume that nodes know their own locations. GPS or some other approximate but less burdensome localization algorithm [3, 7, 16, 17, 20] provides this information. This assumption is crucial for our proposed datacentric storage mechanism. We believe it a reasonable assumption because in many cases the sensornet data are useful only if the locations of their sources are known. We further assume that communication to the outside ....

L. Girod and D. Estrin, Robust Range Estimation Using Acoustic and Multimodal Sensing, In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, (Maui, Hawaii, October 2001).

....of several several other nodes. We further assume that the nodes know their location (in what follows, this can be either their relative or their absolute location) This can be achieved through the use of GPS or some other approximate but less burdensome localization algorithm; see, for example, [4, 11, 22, 23, 25]. This assumption that nodes know their (absolute or relative) location is crucial for our proposed data centric storage mechanism. However, we think it is a reasonable assumption because in many cases the sensornet data is useful only if the location of its source is known; e.g. knowing that a ....

....sensornet deployments precludes manual configuration; several aspects of network and system self configuration are currently active research topics. Important advances have been made in topology self configuration [26, 6] localization (in accurate ranging using acoustic or ultrasound signals [23, 22, 11]) and in location estimation coordination techniques by which nodes can determine their location [4, 25] and post facto low energy time synchronization [9] L3: Packet routing: The MAC layers described above allow nodes within radio range to communicate. Packet routing algorithms are required ....

L. Girod and D. Estrin. Robust Range Estimation Using Acoustic and Multimodal Sensing. In Proceedings of the IEEE Conference on Intelligent Robots and Systems, 2001.

....coherent signal processing. Our system s time synchronization is an implementation of Reference Broadcast Synchronization (RBS) described more fully in [4] Localization is based on an underlying ranging system that works by timing the flight of a wideband acoustic pulse, described in [5]. The remainder of this paper is organized as follows. In Section II, we describe the hardware platforms that compose our testbed. We give an overview of the software components of our system in Section III. A more detailed description of the subsystems is found in Section IV (time ....

....ranging component estimates the distances between nodes in the network. Next, a coordinate system is constructed using the range estimates. The following sections describe each of these components in more detail. A. Acoustic Ranging Our acoustic ranging system, described in more detail in [5], uses a wideband pseudonoise sequence to measure the time of flight of sound from one point to another. In the current implementation, the detector is implemented in software, and requires considerable memory and CPU time (far beyond the capabilities of a Mote) However, the high process gain of ....

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In International Conference on Intelligent Robots and Systems, October 2001.

....time be synchronized more precisely than in traditional Internet applications on the order of 1sec or better due to their close coupling with the physical world and their energy constraints. For example, precise time is needed to measure the time of flight of sound for localizing its source [8]; distribute a beamforming array [30] form a lowpower TDMA radio schedule [2] integrate a time series of proximity detections into a velocity estimate [4] or suppress redundant messages by recognizing duplicate detections of the same event by different sensors [12] Some sensor network ....

....(e.g. precision vs. multihop path length, kernel timestamps vs. userspace timestamps) and in terms of its usefulness in a real system. While we have implemented the multihop algorithm in the current RBS daemon, and indeed depend on it for some of our applications (e.g. acoustic localization [8]) we have not yet systematically characterized its performance. In addition, we would like to characterize the error of a node with respect to UTC when RBS is used to synchronize to that external timescale, as described in Section 5.4. Finally, we would like to extend our experience with RBS to ....

L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

....can be provided by the location support system. For instance, even within the context of wireless sensor networks [2] geographic ad hoc routing requires location accuracy to be on a scale with range, whereas collaborative signal processing applications may require precise position information [3]. Providing precise location information requires dedicated hardware, higher power, extensive pre con guration or centralized approaches. Therefore, a location system may be engineered to support only a certain desired location granularity. Applications with lower granularity requirements can ....

....have high uncertainty along the axis perpendicular to the direction of motion of the observed object whereas bearing sensors have lower uncertainty along this axis. Combined acoustic and radio ranging is a ected by non line of sight conditions, but provides highly accurate line ofsight ranging [3]. The location model could therefore qualify uncertainty along each axis, or provide a probability distribution function (PDF) for location, if a compact representation exists. 2.3 Energy Constraints For several applications, nodes and beacons often need to be small and untethered, imposing ....

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In Proceedings of IEEE/RSJ IROS

....but in terms of named data. 3. Our work also assumes static (i.e. immobile) sensors. This does not simplify the geographic routing problem, but does enable some of the route learning techniques we use. 4. Like previous work, however, we do assume the existence of a localization system [22, 2, 18, 7, 19] that enables each node to know its current position. 5. Motivated by the stringent energy constraint in sensor networks, we use energy aware metrics, together with geographical information, to make energy efficient routing decisions. In previous work, balancing energy usage has not been an ....

....USER. However, their pre built routing table and multi path structure may not scale to large size sensor networks. Moreover, table driven approach may not be able to adapt well to network dynamics or traffic dynamics at a low cost. Localization work There has been substantial research interest [22, 18, 2, 7, 19] in localization systems. Such systems are a prerequisite for geographical routing and other sensor net applications. Of those, Ward et al. 22] propose a ultrasonic location system based on tri lateration principle; Bulusu et al. 2] propose a coarse grained connectivity metric method for ....

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

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L. Girod and D. Estrin, "Robust Range Estimation Using Acoustic and Multimodal Sensing," Proc. IEEE/RSJ Int'l Conf. Intelligent Robots and Systems (IROS 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, Hawaii, Oct. 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2001.

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Girod, L. and Estrin, D., "Robust Range Estimation Using Acoustic and Multimodal Sensing," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

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L. Girod and D. Estrin, "Robust Range Estimation Using Acoustic and Multimodal Sensing," in Proc. IEEE International Conference on Intelligent Robots and Systems, 2001.

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L. Girod, D. Estrin, and et al. Robust range estimation using acoustic and multimodal sensing. IEEE Conference on Intelligent Robots and Systems, 2001.

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L. Girod and D. Estrin, "Robust Range Estimation Using Acoustic and Multimodal Sensing," in Proc. IEEE International Conference on Intelligent Robots and Systems, 2001.

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L. Girod and D. Estrin, Robust range estimation using acoustic and multimodal sensing, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), volume 3, pp.1312-1320, Maui, Hawaii, October 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In Proc. IROS 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSI Int. Conf. on Intelligent Robots and Systems (IROS), 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing.

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Lewis Girod and Deborah Estrin. Robust range estimation using acoustic and multimodal sensing. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2001.

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L. Girod and D. Estrin, "Robust range estimation using acoustic and multimodal sensing," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

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L. Girod and D. Estrin, "Robust range estimation using acoustic and multimodal sensing," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001.

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Lewis Girod and Deborah Estrin. Robust range estimation using acoustic and multimodal sensing. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSI Int. Conf. on Intelligent Robots and Systems (IROS), 2001.

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L. Girod and D. Estrin. Robust range estimation using acoustic and multimodal sensing. In IEEE/RSI Int. Conf. on Intelligent Robots and Systems (IROS), 2001.

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Lewis Girod & Deborah Estrin. Robust Range Estimation Using Acoustic and Multimodal Sensing. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS). IEEE/RSJ, 2001.

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