Bi-Modal Control of Vacuum-Powered Soft Pneumatic Actuators with Embedded Liquid Metal-Based Strain Sensitive Skin

Laurent Mirko Dejace, Stéphanie Lacour, Jamie Paik, Matthew Aaron Robertson
IEEE, 2019
Article de conférence

Résumé

Soft robotic systems are composed of active and passively deformable structures which are intrinsically compliant, flexible, and elastic. Although these features offer benefits of adaptability, robustness, and safety, controlling these types of robots is a significant challenge, in part from the difficulty of obtaining feedback from sensors which provide state information without hindering the advantageous material properties which grant these systems their unique mechanical behavior. We demonstrate here the first integration of a flexible, stretchable, liquid metal-based strain sensor with vacuum powered soft pneumatic actuators (V-SPAs) for simultaneous controlled feedback of the soft actuators as well as user input and soft robotic device interaction. The soft sensors which are encapsulated within a Polydimethylsiloxane (PDMS) membrane are directly embedded in the outer body skin of the soft actuators, and can be used to correlate the deformation of the body under vacuum actuation to overall actuator strain or to detect external disturbances. This information is used to compute and control the angle of a rotational 3-DoF actuator module, as well as detect implicit user input control signals by direct interaction without the need for an external control interface. The dual use of embedded sensing shown in this work provides a fundamental strategy for soft collaborative robot applications.

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https://infoscience.epfl.ch/record/265361?ln=fr

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Laurent Mirko Dejace, Stéphanie Lacour, Jamie Paik, Matthew Aaron Robertson
IEEE, 2019
Article de conférence

Résumé

Official source

https://infoscience.epfl.ch/record/265361?ln=fr

À propos de ce résultat

Concepts associés (9)

Concepts associés

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Publications associées (11)

Publications associées

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Noise radiated by different industrial structures that surround us in daily life are more and more considered as environmental pollution. Standards defining a tolerable sound level for each of these noise sources are regularly called into question and respecting them becomes an additional constraint for manufacturers. The last decades have seen the increasing development of means used to fight these noise disturbances. The wide diversity of noises perceived as harmful has contributed to the progressive increase in specificity and efficiency of solutions proposed to reduce the disturbances. For some applications, passive solutions, based on the use of materials capable of absorbing or deviating acoustic or vibratory waves, have progressively been replaced by "active" solutions, based on the generation of an acoustic wave of opposite phase to the disturbing one radiated by the noise source. Power transformers are sources for which passive solutions (anti-noise walls) are usually expensive and not very efficient, particularly at low frequency. Furthermore, characteristics of noise radiated by transformers (low frequency tone noise) are such that they are particularly well suited for the implementation of an active solution. Typically, an active control system dedicated to transformers (feedforward) is composed of actuators, used to generate the anti-noise and usually located near the tank, sensors, used to measure the attenuation obtained and to provide a reference signal, and a controller used to drive the actuators as a function of the information collected by the sensors. When the sensors are microphones, they are usually moved away from the noise source, in such a way that they pick up acoustic pressure that is representative of the noise propagated far away. In the vicinity of the source, local acoustic phenomena can occur which are not propagated far away. A microphone located near the noise source would therefore pick up an acoustic pressure that did not necessarily represent the one that effectively exists far away, the area where we are in fact seeking to reduce the noise. These phenomena, frequently grouped under the term "nearfield" tend to decrease the performance of the control system, owing to the fact that the controller seeks in this case to reduce an acoustic pressure which is not representative of the noise to be reduced. In practice, the significant amount of wiring required as a result of the positioning of the microphones in the far field, has a non-negligible effect on the cost of the system. The possibility of bringing the sensors closer to the source is sufficiently advantageous to envisage to studying the feasibility and the resulting consequences. The present approach consists in representing the primary field radiated by a vibrating structure in terms of a set of "acoustic radiation modes". The use of radiation modes to characterise the behaviour of a structure has received increasing attention since the beginning of 90's, especially for active control applications. Usually, this approach consists in representing the radiated power in terms of a set of surface velocity distributions, called radiation modes, that have the property of radiating independently of each other. Radiation modes result from diagonalization of a discrete expression of the radiation operator. We propose here to study the consequences on the radiation modes of a structure from bringing the microphones closer to it. We will study how the acoustic field varies with the distance and how this can be used to obtain a model, the complexity of which is adapted to the observation distance.

EPFL2001

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The MOVE System: Monitoring of waste collecting vehicles

Telmo Cunha, Phillip Tomé

Nowadays, efficiency and productivity are fundamental concepts, in any kind of business. Although one can easily accept this as a known fact, one cannot easily identify which steps must be taken to achieve these goals. One approach consists of taking full advantage of the assets already available in the company, be they manpower or equipment. One kind of business that is strongly exposed to this problem concerns urban waste collecting. In this case, the productivity of the company can increase substantially if good fleet management policies are followed. Being aware of this fact, GEONAV has developed a fleet management system, named MOVE (Vehicle Monitoring), which is based on GPS. Each vehicle is equipped with a small onboard computer that includes, in the less complex model, a 12 channel GPS receiver and a GSM module. To cope with the problems usually affecting GPS in urban environments, such as having few satellites in view and multipath due to urban canyons, the system can incorporate information from low cost dead-reckoning sensors, such as the vehicle odometer and a gyroscope. Furthermore, other features can be added to the system, by using information from sensors readily available in the vehicle or that are installed specifically for the task intended. For instance, through a keypad unit, the driver can identity itself, by inserting a specific code or input the amount of fuel supplied to the vehicle. In addition, the system can automatically count the number of waste bins emptied, the number of times the vehicle has disposed of its waste in the wasteland or determine in real-time the vehicle’s weight. All information is sent to a Control Center using GSM or is stored in the computer’s memory, for a later download. In this case, an alternative means of transmission besides GSM can be used, namely a short range radio. Since no costs are involved when using this radio system, the exploitation costs of the MOVE system are greatly reduced. The Control Center software is based on a client/server architecture. The server application is responsible for controlling the communications between the Control Center and the vehicles and for storing all data received in a central database. The client applications connect to the server application, using the intranet, and are based on the GIS ArcView 8.x platform. Using a client application, an operator can visually determine the fleet status over a map or other type of visual representation. To reduce exploitation costs of the system, the status of the fleet is obtained by using SMS messages to exchange data between the vehicles and the Control Center. However, the option to follow a particular vehicle, by establishing a GSM call, is also possible. In this case, the position of the vehicle is updated at 1 Hz. The information that is stored in the database is organized in such a way as to allow the calculus of several statistical parameters that are useful to the management and control of the fleet. For example, one can determine the amount of kilometers driven, the time to complete a particular waste collection circuit, the fuel consumption, the number of waste bins emptied and their location, the number of times the vehicle was emptied of its waste, the vehicle’s weight, etc. This information can be used to establish new and better policies to enhance the fleet’s productivity and to present a better service to the end customer. This paper describes in detail the architecture of the MOVE system and its functionalities, including both the equipment installed onboard the vehicles and the Control Center’s software. Emphasis is given to the system’s flexibility to be used in different case scenarios, besides the monitoring of waste collection vehicles.

2003

Chargement

Error handling in multimodal voice-enabled interfaces of tour-guide robots using graphical models

Plamen Prodanov

Mobile service robots are going to play an increasing role in the society of humans. Voice-enabled interaction with service robots becomes very important, if such robots are to be deployed in real-world environments and accepted by the vast majority of potential human users. The research presented in this thesis addresses the problem of speech recognition integration in an interactive voice-enabled interface of a service robot, in particular a tour-guide robot. The task of a tour-guide robot is to engage visitors to mass exhibitions (users) in dialogue providing the services it is designed for (e.g. exhibit presentations) within a limited time. In managing tour-guide dialogues, extracting the user goal (intention) for requesting a particular service at each dialogue state is the key issue. In mass exhibition conditions speech recognition errors are inevitable because of noisy speech and uncooperative users of robots with no prior experience in robotics. They can jeopardize the user goal identification. Wrongly identified user goals can lead to communication failures. Therefore, to reduce the risk of such failures, methods for detecting and compensating for communication failures in human-robot dialogue are needed. During the short-term interaction with visitors, the interpretation of the user goal at each dialogue state can be improved by combining speech recognition in the speech modality with information from other available robot modalities. The methods presented in this thesis exploit probabilistic models for fusing information from speech and auxiliary modalities of the robot for user goal identification and communication failure detection. To compensate for the detected communication failures we investigate multimodal methods for recovery from communication failures. To model the process of modality fusion, taking into account the uncertainties in the information extracted from each input modality during human-robot interaction, we use the probabilistic framework of Bayesian networks. Bayesian networks are graphical models that represent a joint probability function over a set of random variables. They are used to model the dependencies among variables associated with the user goals, modality related events (e.g. the event of user presence that is inferred from the laser scanner modality of the robot), and observed modality features providing evidence in favor of these modality events. Bayesian networks are used to calculate posterior probabilities over the possible user goals at each dialogue state. These probabilities serve as a base in deciding if the user goal is valid, i.e. if it can be mapped into a tour-guide service (e.g. exhibit presentation) or is undefined – signaling a possible communication failure. The Bayesian network can be also used to elicit probabilities over the modality events revealing information about the possible cause for a communication failure. Introducing new user goal aspects (e.g. new modality events and related features) that provide auxiliary information for detecting communication failures makes the design process cumbersome, calling for a systematic approach in the Bayesian network modelling. Generally, introducing new variables for user goal identification in the Bayesian networks can lead to complex and computationally expensive models. In order to make the design process more systematic and modular, we adapt principles from the theory of grounding in human communication. When people communicate, they resolve understanding problems in a collaborative joint effort of providing evidence of common shared knowledge (grounding). We use Bayesian network topologies, tailored to limited computational resources, to model a state-based grounding model fusing information from three different input modalities (laser, video and speech) to infer possible grounding states. These grounding states are associated with modality events showing if the user is present in range for communication, if the user is attending to the interaction, whether the speech modality is reliable, and if the user goal is valid. The state-based grounding model is used to compute probabilities that intermediary grounding states have been reached. This serves as a base for detecting if the the user has reached the final grounding state, or wether a repair dialogue sequence is needed. In the case of a repair dialogue sequence, the tour-guide robot can exploit the multiple available modalities along with speech. For example, if the user has failed to reach the grounding state related to her/his presence in range for communication, the robot can use its move modality to search and attract the attention of the visitors. In the case when speech recognition is detected to be unreliable, the robot can offer the alternative use of the buttons modality in the repair sequence. Given the probability of each grounding state, and the dialogue sequence that can be executed in the next dialogue state, a tour-guide robot has different preferences on the possible dialogue continuation. If the possible dialogue sequences at each dialogue state are defined as actions, the introduced principle of maximum expected utility (MEU) provides an explicit way of action selection, based on the action utility, given the evidence about the user goal at each dialogue state. Decision networks, constructed as graphical models based on Bayesian networks are proposed to perform MEU-based decisions, incorporating the utility of the actions to be chosen at each dialogue state by the tour-guide robot. These action utilities are defined taking into account the tour-guide task requirements. The proposed graphical models for user goal identification and dialogue error handling in human-robot dialogue are evaluated in experiments with multimodal data. These data were collected during the operation of the tour-guide robot RoboX at the Autonomous System Lab of EPFL and at the Swiss National Exhibition in 2002 (Expo.02). The evaluation experiments use component and system level metrics for technical (objective) and user-based (subjective) evaluation. On the component level, the technical evaluation is done by calculating accuracies, as objective measures of the performance of the grounding model, and the resulting performance of the user goal identification in dialogue. The benefit of the proposed error handling framework is demonstrated comparing the accuracy of a baseline interactive system, employing only speech recognition for user goal identification, and a system equipped with multimodal grounding models for error handling.

EPFL2006

Chargement

Error handling in multimodal voice-enabled interfaces of tour-guide robots using graphical models

Plamen Prodanov

EPFL2006

The MOVE System: Monitoring of waste collecting vehicles

Telmo Cunha, Phillip Tomé

2003

EPFL2001