Wireless Sensor Networks and Safe Protocols for user tracking inHuman-Robot Cooperative workspaces

Federico Vicentini1, Massimiliano Ruggeri2, Luca Dariz2, Alessandro Pecora3,Luca Maiolo3, Davide Polese3, Luca Pazzini3 and Lorenzo Molinari Tosatti1

Abstract— Workers protection in collaborative industrialrobotics application represents the predominant aspect of robotsafety in production systems. Flexible production systems andmultimodal human-robot interactions often encompass coop-erative tasks that are performed in fenceless configurations.Collaborative open workspaces enable, in fact, a workflow ofcontinuously interchangeable tasks done by operators or byrobot at close distance or using hand-guided modes. Layoutand workflow optimization may, in fact, require a co-presencein some shared spaces whose safeguarding (e.g. robot speedlimitations, distances) is conservatively restricted by the currentstandards. In such scenarios, the tracking of operators ismandatory for the overall assessment of the system safety. Inthis work, a combination of wireless sensing technologies, highlyrobust wireless protocols and safe computation over a standardethernet IP (black channel) concur to improve the functionalsafety of a cooperative robotic system. The system architectureand data framework are in particular discussed with referenceto the properties of the communication protocols implementingthe safety layer.

I. INTRODUCTION

Safety of workers and devices is a primary requirement forany robotic system. Safety can be generally introduced asthe set of actions, settings, countermeasures and behaviorsadopted by systems, users and operators for preventinghazards.Collaborative-robotics applications (Fig. 1) in the sense ofISO 10218-2[1] must provide such operational safety, en-abling robot controlled stops on contact force or distancethresholds and speed limitation based on the safe knowl-edge of the robot status (safe robot hardware accordingto ISO 10218-1 standard [2]). The detection/prevention ofhazardous transfer of energy from robots to users1 is ofundeniable importance for platforms natively dedicated tosafe physical human-robot interaction [4]. Limits for injuryin contacts or impacts are, in fact, under discussion inISO TS 15066 [5], while candidate platforms for such kindof interaction include, for instance, robots with compliantactuation systems [6], [7], [8] and lightweight platforms [9],[10] variably attaining compliant behavior by mechanics andcontrol. Nonetheless the same safety properties apply forcollaborative systems involving also industrial robots.

1 National Research Council of Italy (CNR), Institute of IndustrialTechnologies and Automation (ITIA), via Bassini 15, 20133 Milan (I)

2 National Research Council of Italy (CNR), Institute of Earth MovingMachines (IMAMOTER), via Canal Bianco, 28 - 44124 Cassana (I)

3 National Research Council of Italy (CNR), Institute of Microelectronicsand Microsystems (IMM), via del Fosso del Cavaliere 100, 00133 Rome (I)federico.vicentini@itia.cnr.it1see [3] for an analysis of energy transfer in impacts and hazard indexing

In collaborative scenarios featuring workspace sharing andhand-guided robots, the primary purpose of current standardsis to monitor/keep safe distances and velocities between usersand robots and to monitor velocities and forces, respectively.Safety is therefore based upon a fail-safe knowledge ofthe robot positioning and the user-robot mutual positioning.Traditionally, safe workspace monitoring has been restrictedto the use of certified (e.g. ISO 13489-1:2006 PerformanceLevel (PL) e [11], or equivalent IEC 61508 SIL 3 [12])sensors. Eventually, the certification compatibility inherentlyrestricts the detection output to a logical (i.e. safe boolean)condition upon the human/device presence in an offline-validated volume around the robot. Such normative pro-cedure excludes the online update of a dynamic safetydistance (i.e. nonsafe float value) in terms of either a variablethreshold for emergency states or the continuous monitoringof moving objects (e.g. operators) within the workspace.

One of the main motivations in robot system integrationfor safety, including the present work, is therefore to en-able the technological capability in monitoring some safetyparameters, like distances, subject to variable thresholding.Beneficial scenarios include, for instance, the computationof safe collision avoidance strategies in a given local con-figuration of the robot, while predefined safety volumes(ISO TS 15066) have to conservatively consider an envelopeof the robot workspace. Entering a safeguarded area, infact, unnecessarily stops any robot motion also in subsets

Fig. 1: Cooperation task typologies repictured from Ap-pendix E (pp. 53/54) of the Standard EN-ISO10218-2/2011.All rights reserved.

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Fig. 2: a robotic distributed system including both safe andunsafe nodes/devices.

of its workspace where minimum distances are nonethelessrespected.Other scenarios may include the continuous safe monitoringof the user in hand-guided robot operations in automaticspeed mode2.In all these scenarios, one of the prominent requirementsis the safe monitoring of users, which involves sensors andarchitectural aspects (e.g. protocols and buses) for tracking.In terms of architectures, in fact, sensing is often distributedmay require some significant computational power in in-formation runtime processing. The resulting paradigmaticdistributed [14] system (Fig. 2) is therefore a network ofsafety-dedicated devices, possibly including non-natively-safe nodes and where safe/unsafe controllers are parts of awider set of data producers/consumers. Hardware/softwarecomponents dedicated to safety in the operational senseintroduced above, have to be designed and evaluated accord-ing to the principles of functional safety [12], i.e. how toreasonably reduce the risks associated with failures in oneor more such system components.

The present work is dedicated to the architectural prop-erties, most notably the communication protocols, of an

2the robot proper has to be compliant with standards for hand-guidedoperations in both manual and automatic modes

Fig. 3: Wireless-based positioning solutions [13]

application in user localization through tracking sensors.User tracking is performed through Wireless Sensor Network(WSN) nodes interconnected with nodes dedicated to safetyfunctions (e.g. computation of the safe distances to robot).In particular, the tracking algorithm is performed throughthe nodes’ signal strength (RSSI), preliminarily neglectingthe eventual sensors payload. Alternatively to device-freelocalization (DFL) methods or 3D vision-based systems(e.g. RGB-D, time-of-flight, etc), this study considers theavailability of a source of radio frequency (RF) attached tothe body of an operator in an industrial scenario. Despitethe actual wearability and feasibility of the solution underdiscussion, the usage of some sources of signal directlyassociated with the operator has to be considered for thepotential diversity and sensor fusion of the multiple sourcesavailable at shop floor. Industrial environments are, in fact,hardly suitable for single sources of environmental informa-tion because of the variabiliy of conditions, which possiblychallenge some intrinsic weaknesses (e.g. occlusions andvariable lighting conditions for image-based systems, needof frequent calibration and tuning). Additionally, sensoryequipment able to provide disturbance-(almost)free mappingof the environment (e.g. LIDARs) may represent a majorinvestment factor in real plants. Low-cost detection systemsfor safety are, in fact, very much demanded for a number ofeasy deployable and reconfigurable robotic applications. Theselection of the actual wireless protocol to be introduced inthe safety solution is mainly based on the criteria of weara-bility (i.e. limited payload on garments, power constraints),optmization for low-range applications (i.e. availability ofsignal, reliability of connection) in indoor conditions andability to provide accurate localization.Considering the benchmarking in [13] (see Fig. 3) andpower consumption experiments in [15] (see Fig. 4), theWSN used for user localization is based on IEEE 802.15.4.Although functionally well suited for indoor application andarchitecturally scalable over a large number of nodes, thereliability of the WSN subsystem has a substantial influenceon the overall system safety. Wireless protocols used forWSNs at large are, in fact, mostly designed for distributedinformation systems and distributed commands, without spe-cific requirements for safety. Moreover such protocols are

Fig. 4: comparison in power consumption among somepopular wireless protocols [15].

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Fig. 5: General purpose safety architecture (left), showing the main communication network black channel for both safe andunsafe data exchange. Actual implementation of a safety solution with Ethernet POWERLINK as the main SRP/CS blackchannel and low-end protocols as additional black channels (right). Second source of target sensing - necessary to grantSIL3 class with DC < 99% or PLd - is depicted in light gray.

not deterministic and protocol procedures (e.g. arbitration,collision management, retransmission and delayed commandhandling) are rarely critical in most of known applications(market and/or literature). Recent studies analyzed both theenergy consumption and the real time calability of some mostcommon wireless protocols (Bluetooth and Zigbee) [16] inmachine-to-machine setups. On the contrary, user trackingfor safety requires high reliability both on data treatment andthe protocol itself, in order to attain the functional safety ofthe wireless communication channel.

The paper introduces some architectural considerationsabout the protocols relaying the sensing information fromWSN sensors to the Safety-Related Part of the ControlSystem (SRP/CS) supervising the functional safety of thesolution. The use of WSNs, in fact, belong to the class ofsolutions integrating general purpose sensors over commonphysical layers in safety applications.

II. SYSTEM ARCHITECTURE AND PROTOCOLS

SRP/CS processing units (e.g. safe PLCs, safe drivers) arestandard-wise implemented with a redundant hardware ar-chitecture. However, the physical layer in connecting safety-related units is not necessarily required to be duplicated inorder to attain a safe communication network (black channelapproach, introduced in IEC 62280-1). Intrinsically unsafechannels (e.g. conventional networks, automation filedbuses)may be used as a safety-unaware transport layer on top ofwhich a safety layer is added in order to connect safety tasks.

The safety stack implements safety-related transmissionfunctions and monitors the integrity of the communicationchannel (see Fig. 5). One of the advantages of the blackchannel principle is to share the standard communicationnetwork (usually already available at shop floor) for both safeand unsafe (e.g. asynchronous diagnostics, logs) tasks and,more importantly, to allow devices compatible with standardnetworks (e.g. ethernet IP) to be used in SRP/CS of classSIL2 or PLd. The template safety architecture of Fig. 5-left-top depicts, in fact, the use of any supervised fieldbus(clocked by a Master Node) to provide the black channelwhere safety-related information is treated.The condition to meet is to ensure the access to the safetytasks – performed by processing units (safe CPUs) – fromany node of the network, implementing the correspondingsafety stack. The safety stack has the role of seamlesslyconnecting all safety-related processing units through theimplementation of some safety functions in the given pro-tocol. The safety functions operating through the blackchannels require a full degree of verification of passingmessages (i.e. medium/high diagnostic coverage (DC)) asin Fig. 7. Similarly, any node (e.g. Slave) in the networkgranting access to the black channel, can gateway the inputinformation from sensors according to the same principle.Depending on the hardware implementation of the withstand-ing sensory equipment, the safety rate can range from SIL2 to3, depending on the redundancy of interfaces and dedicatedchannels (equivalently, single/dual channels in ISO 13489-

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1:2006 with variable DC rate). Highly available local net-works could implement, for instance, the IEC 62439 ParallelRedundancy Protocol (PRP) [17] with an extra duplicationof the polling nodes provided by a pair of Slave nodes (seeFig. 5-right).

In the present tracking application (see detection of thetarget in Fig. 5), the information has to pass through multipleprotocols in order to being used in safety functions (insafeCPU), ultimately enabling the safe I/O. All protocols arerequired to be suitable for providing a consistent black chan-nel for the upstream data. The following sections describe theactual wireless and wired protocols used for implementingthe safety solution.

A. Modified IEEE 802.15.4

The WSN subsystem can be classified as fail silent, and incase of absence of communication or in case of a low qualitycommunication due to a disturbed channel, the system canbe stopped safely. So the most important characteristic of thecommunication protocol is to provide a robust communica-tion protocol in terms of both real time and data integritycontrol up to the safeCPU. The Wireless communication fora safety critical industrial application shall therefore providea star topology, shall support channel diversity and TimeDivision Multiple Access (TDMA) and shall manage Highpriority and Low Priority Traffic. The chosen 802.15.4eLLDN mode communication, as described in [18] and itsamendment [19], offers a bidirectional communication be-tween a Coordinator node and some other (slave) nodes,creating a time-slotted and/or multi-channel communicationto reduce or overcome some of the unpredictable latenciesthat common CSMA/CA introduces; however this communi-cation is intended mostly for data communication from nodesto Coordinators, e.g. for sensor data acquisition. The standardprotocol does not offer high priority communication slotsfrom from Coordinator to slave nodes, nor presents deter-ministic packets in the communication from the Coordinatorto the slaves in spite of having both deterministic and CSMApackets on the dual way. Even the real time performace isunderefficient because of a rule for packet size, which mustbe a multiple of a defined slot that uselessly increases theSuperframe size. Then for real time and safety purposes,

Fig. 6: IEEE 802.15.4 LLDN superframe format: standard(top) and modified (bottom)

Nodes Standard LLDN Modified LLDN10 22.1 17.320 41.3 32.7

TABLE I: Superframe length (ms) with 15 byte/pkt uplink,3 byte/pkt downlink, 2 byte/pkt for low-priority traffic.

Fig. 7: sources of error messages on black channels andimplemented countermeasures.

the protocol was redesigned ensuring a bidirectional timedslot communication and an increased real time availability,due to a shortened Superframe obtained with a differenttimed slot size management [18]; some numeric results aredepicted in Table I. From the safety point of view, thecommunication is made more reliable both on the acknowl-edge of messages and on the confidence of correctness ofreceived information. This result was achieved includingsome explicit acknowledgement for inward/outward criticalinformation and adopting countermeasures to avoid the mostcommon communication errors. The full countermeasures listis reported in Fig. 7 and the current adopted choices aremarked. Then, the Superframe of the 802.15.4e (Fig. 6-top)is re-engineered, with the Coordinator starting the commu-nication but both coordinator and nodes (slave) using highpriority slots for safety relevant data. Additionally, for eachgroup of data transmitted a running number is added in eachUTS (Uplink Time Slot), and in the added DTS (DownlinkTime Slot) for safety relevant data from the Coordinator,and additional CRC for each group of data is included inthe frame. The modified LLDN mode Superframe (Fig. 6-bottom) helps in defining precise timing for packets using theBeTS slot features and role, so the Time Stamp and TimeExpectation countermeasures are easy to be implementedfor each node. The packet reception acknowledgement isprovided in a timed slot for the consumer in the subsequentmessage after the request for command from the producerunit (see Fig. 7).

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Fig. 8: deployment of safety system over standard connection networks.

B. Wired protocols

The interfaces between components are de facto designedand implemented as real-time synchronous data exchangemethods, based on selected protocols. In the case of Ethernet-based communications, the ad-hoc black channel from sensormodules and the main fieldbus (see Fig. 5-right) is a UDP/IPfull stack on top of which an application layer enablesa fail-safe data exchange. In this case, the black channelprinciple is applied over the entire ISO/OSI stack througha set of application methods running in real time on thenode where critical accesses to the network sockets areimplemented (bus slave, i.e. EPL controlled node). Methodsfor monitoring/verifying some possible message failures (seeFig. 7) are, in fact, implemented as sender/receiver logicalcomponents in connected UDP peers. In a star architecture,the parent black channel (i.e. EPL) slave is, in fact, thecentral receiver and evaluator of all data exchanges. Theinterface proper is therefore coincident with the datagramdescription used for connecting different components. Beingall components modular and independent in implementationand target compilation (OS-independent), the only standard-ized/shared information (e.g. interface) is the packet/payloaddeclaration. The main black channel is in this case one ofthe standard industrial communication fieldbused (EthernetPOWERLINK) able to provide certified safety functions athardware and software level.

III. EXPERIMENTAL SETUP IMPLEMENTATION

The architecture depicted in Fig. 5 featuring several blackchannels for safety-related wireless-based user tracking, isdeployed in a real fenceless robotics setup (Fig. 8). Theactual WSN-based localization system was selected for wear-ability comfort due to the size and weight of the sensingelements: a commercial device Zolertia z1 was chosen asthe core node of the WSN. This is a low-power moduleof small size (34.5x56.8mm), based on a TI MSP430 C-programmable microcontroller and equipped with a ZigBeetransceiver and an integrated ceramic antenna. The CC2420transceiver [20] at 2.4GHz has a communication band of

250 kbps. The module is fully expandable thanks to thenumber of ports available (USB , I2C , SPI, 2xUARTs), suchthat external inertial sensors and other devices can be easilyconnected for use of payload data in addition to the RSSI-based localization. Moreover, due to the relative simplicityof its electronic circuits and its open source code, the local-ization device can be further miniaturized and integrated onflexible PCBs, thus allowing a fully integration in the workergarments (Fig. 9). The wireless localization algorithm is

Fig. 9: A concept for embedding a mobile WSN node andadditional sensors in garments.

based on a lateration3 algorithm between the wearable nodeand a set of fiducial anchor nodes of known position withinthe layout. In order to avoid possible power losses due to thepresence of obstacles in the shared workplace a redundantnumber of anchor nodes was distributed in the workspace (upto 8). The localization technique is based on a triangulationmethod, based on the distances among the target and atleast three non-collinear reference anchors. The estimationof the mutual position of mobile elements (distances) isrelated to Received Signal Strength Indication (RSSI). It isworth to note that the most recent RF transceivers have anintegrated module that estimates the RSSI, moreover, ZigBee

3localization algorithms can be classified in lateration and angulationalgorithms according to the type of measurement that has to be performedbetween mobile and anchor nodes, distances or angles, respectively.

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protocol 802.15.4-2012 uses RSSI as indication data stan-dardizing also the RSSI measurement [21]. The localizationalgorithm includes a two-steps procedure: first (ranging),the distances between the reference nodes and the mobilenode are evaluated using the variation of the RSSI [22].Additionally, a compensation algorithm of the RSSI valueis used to reduce the errors in the RSSI measurements dueto the antenna misalignment [23]. Finally (positioning), anoptimization algorithm is used to evaluate the 3D coordinatesof the mobile nodew.r.t. the fiducials coordinates [24].A preliminary calibration procedure (30 samples over a 15m2 area) resulted in RMS of about ±25 cm using only 3anchor nodes and neglecting the on-board inertial sensors.

IV. CONCLUSIONS

WSN for user tracking in shared robotic workspaces has beenintroduced as a possible source of environmental informationto be fused with other technologies for the safety estima-tion of hazardous conditions in collaborative tasks. For thepurpose of providing a consistent solution for safety-relatedoperations (according to functional safety standards), somearchitectural considerations have been introduced in orderto deploy safety-related information from unsafe sources tosafe I/Os. Some of available network protocols, remarkablysuitable for low-cost easy integration of general purposesensors, are used as black channels for connecting safe pro-cessing units, ultimately in charge of enabling the requiredprotection degree. The modified WSN protocol, in particular,increases significantly the channel real time and suitabilityfor upgrading/preserving the overall Safety Integrity Level.The enhanced protocol, in fact, bridges some gaps in theservice availability of 802.15.4 protocol in safety-relevantsolutions in industrial applications.While a full risk assessment procedure has to consider theanalysis of faults and related severity, some functional safetyconsiderations for communication protocols are consideredbeneficial because of the implementation of monitored (i.e.safe) failure modes, instead of unrecoverable dangerousfailure modes, in standard communication networks.

ACKNOWLEDGMENTS

This work has been partially supported by CNR FlagshipProgram “Fabbrica del Futuro”, FdF-SP1-T3.1, Project FAC-TOry Technologies for HUMans Safety.

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