InGaAs/InP SPAD with Monolithically Integrated Zinc-Diffused Resistor

Afterpulsing and optical crosstalk are significant performance limitations for applications employing near-infrared single-photon avalanche diodes (SPADs). In this paper, we describe an InGaAs/InP SPAD with monolithically integrated resistor that is fully compatible with the planar fabrication process and provides a significant reduction of the avalanche charge and, thus, of afterpulsing and optical crosstalk. In order to have a fast SPAD reset (<50 ns), we fabricated quenching resistors ranging from 10 to 200 k\Ω, smaller than what is available in the literature. The resistor, fabricated with the zinc diffusions already used for avoiding premature edge-breakdown, promptly reduces the avalanche current to a low value ∼ 100~ μ A in less than 1 ns, while an active circuit completes the quenching and enforces a well-defined hold-off. The proposed mixed-quenching approach guarantees an avalanche charge reduction of more than 20 times compared with similar plain SPADs, enough to reduce the hold-off time down to 1 μ s. Finally, a compact single-photon counting module based on this detector and featuring 70-ps photon-timing jitter is presented

Active Sensing For Touch-based Object Localisation

This doctoral thesis improves the way robots exploit their force and tactile sensing capabilities in order to localise objects in their surrounding, with specific focus on industrial relevance, that is minimising execution time and working with items of real-world geometric complexity. Driven by the need to analyse the decision-making process occurring during localisation operations, we present a test carried out to observe human approach to touch-based localisation tasks. Common behaviour patterns among the subjects were observed, such as following the same sequence of actions and being attracted by specific features of the object. Generalising from relevant literature works, an Active Sensing Task model is elaborated based on five modelling concepts: configuration space, information space, action space, inference scheme and action-selection scheme. Concrete examples from the literature conforming to the model are presented. In this modelling context, an action-selection algorithm named act-reason is developed providing a configurable trade-off between information gain, cost of motion-execution and computation. Inspired by the results of the human experiment, DOF Decoupling is introduced as a methodology to describe localisation applications as coordination of active-sensing tasks with different configuration spaces. This allows the robot to reduce the complexity of the problem, thus improving the online-feasibility of the localisation application. Previous touch-based object-localisation works conform to this methodology, and concrete examples from the literature are provided. A 3DOF rectangle localisation on top of a table is carried out to validate the effectiveness of DOF Decoupling in reducing the complexity of the application. Specifically, the scheme observed in the human experiment is applied to decouple the whole application into an initial 2DOF table exploration task and a 3DOF localisation task after the first contact. Since the complexity of the configuration scales exponentially in the number of degrees of freedom and affects that of the inference scheme, pose estimation in 2DOFs is significantly less computationally expensive than in 3DOFs. Intuitively, to speed up the computation, DOF Decoupling allows the robot to set the pose estimator at the most appropriate level of resolution, i.e. coarse with high uncertainty and fine with low uncertainty. Examples with initial uncertainty up to [0.8m,0.8m,180deg] are presented. The time required to accomplish the localisation with and without decoupling is compared showing a significant improvement in the former case. To assess the robustness of our measurement model and inference scheme in an industrial context, we localise objects up to industrial-relevance complexity using a Staubli RX90 robot equipped with a spherical end effector coupled with a force-torque sensor. Case-study implementations are presented to show how the act-reason algorithm can be effectively adopted to reduce the time to localise an object. In particular, in the proposed examples, the allocated time to reason and act is a function of the current uncertainty. Improvements upon naive strategies are reported in terms of the total time required by the application.status: publishe

Charge Persistence in InGaAs/InP Single-Photon Avalanche Diodes

We present a detailed characterization and modeling of the charge persistence effect that impacts InGaAs/InP single-photon avalanche diodes. Such phenomenon is due to holes that pile-up at the heterointerface outside the active area and has two main consequences: 1) higher noise (equivalent to higher dark count rate), not decreasing as expected at low temperature and 2) possible distortion of the acquired time-resolved waveforms (due to such signal-correlated noise). We propose a model that describes: 1) the generation of holes at the detector periphery in the InGaAs layer; 2) their accumulation at the heterointerface; 3) their subsequent diffusion toward the active area within the InGaAs layer; and 4) their resulting drift to the high field depleted InP region, where the unwelcome spurious avalanche is eventually triggered. We support our model by detailed experimental measurements and simulations. Finally, we propose simple approaches for designing detectors less sensitive to this type of noise

Low-Noise, Low-Jitter, High Detection Efficiency InGaAs/InP Single-Photon Avalanche Diode

We present the performance of a novel InGaAs/InP single-photon avalanche diode (SPAD) with high detection efficiency and low noise thanks to the improvement of Zinc diffusion conditions and the optimization of the vertical structure. The 25-μ mactive-area diameter detector, operated in gated-mode with ON time of tens of nanoseconds, shows very low dark count rate (few kilo-counts per second at 225 K and 5 V of excess bias), 30% photon detection efficiency at 1550 nm, low afterpulsing, and a timing response with less than 90-ps full-width at half maximum and very fast exponential tail (time constant ∼ 60 ps). Therefore, this InGaAs/InP SPAD is among the best ones ever reported in the literature

Action Selection for Touch-based Localisation Trading Off Information Gain and Execution Time

In the context of touch-based object localisation, solving the problem of "where to sense next" is a challenging task due to the curse of dimensionality related to belief-state reasoning. We present a constrained optimisation scheme that computes the next best action maximising the trade off between (i) the localisation information gain, (ii) the time required for its computation, and (iii) the motion-execution time. This allows the robot programmer to have a deterministic influence on the length of every sensing action. The proposed methodology is applied to localise a solid object in 3D using a Staubli RX90 robot equipped with a force-torque sensor coupled with a spherical end effector. A case-study comparison of the task executed with two different time constraints is presented.status: publishe

DOF-Decoupled Active Sensing: A (more) human approach to localization tasks

In the context of scene-model calibration, different forms of sensing may allow to widen the set of environment conditions in which the task can be accomplished. Specifically, in the case of harsh structured intervention scenarios, e.g. seabed or mine sites, the use of cameras may not suffice to perform the calibration due to noise and obstructions. Motivated by such practical problems, our research aims at finding solutions to perform the calibration in different environment with variable initial uncertainty. In particular, we focus on force sensing as it is applicable in highly-soiled environments. The state of the art on touch-based localization provides solutions to low-dimension problems, since the initial uncertainty is bounded by the computational complexity that scales exponentially with the number of considered degrees of freedom. Therefore, previous related works tackled problems with initial uncertainty in the order of 0.5m in translation. Moreover, the question of “where to sense next” remains mostly unsolved, especially for online applications. Driven by the need to find feasible solutions for the decision-making side of the problem and aiming at tackling tasks with high initial uncertainty, a test with thirty human subjects has been performed to observe men and women performing a blind localization task. The subjects had to localize a solid object by exploring a structured environment using a stick, wearing thick gloves, a headset and an eye-cover, so all the senses apart from force sensing were shut down. The experiment showed how all the subjects freely decided to decouple the task into a series of subtasks, each of them focused on a limited number of degrees of freedom. Further to the results obtained in the experiment, a new formulation for localization has been proposed here, named DOF-Decouple Active Sensing. In particular, the global task is decoupled into a series of subtasks aimed at solving only a part of the global uncertainty. This allows to keep the problem tractable for online applications as both the number of considered degrees of freedom and the estimator resolution is increased while the uncertainty is being reduced. Moreover, the decision-making about “where to sense next” is formalized as a greedy POMDP with a reward function that takes into account the expected information together with the cost of motion and the computational effort to process the obtained information. To demonstrate the applicability and the computational benefits of the proposed decoupling scheme, a series of touch-based rectangle localization in 3D has been simulated with initial uncertainty of 2m in translation and 180deg in rotation. A robotic implementation of such application is currently under development. The proposed scheme introduces a high-level decision making step that simplifies the global localization problems into subtasks, then allows to choose which action to do evaluating both benefits and drawbacks. Such formalization is suitable for integrating multiple sensors and making decisions about which one to use. Therefore, the application of such scheme to a multi-sensor system is currently being investigated. In particular, we intend to show the effectiveness of the decision-making among different sensing actions. Moreover, the hierarchical problem decoupling followed in the implemented application is taken as-is from the human experiment. Although, further to the observed results, it is evident that the subjects decided which DOFs to tackle in which subtasks by prioritizing the different scene objects based on their topological relationships. Hence, the possibility of formalizing such decoupling as a constraint optimization using object properties and relative constraints is to be further investigated.Interactive Presentationstatus: accepte

DOF-Decoupled Active Force Sensing (D-DAFS): A Human-Inspired Approach to Touch-based Localisation Tasks

In the context of touch-based object localisation in structured environments, solving the full 6D problem is computationally expensive as complexity scales exponentially with the number of degrees of freedom. Previous related works provided solutions to problems whose initial uncertainty was bounded by the computational feasibility for on-line applications. Observing the results of an experiment in which human beings face a blind localisation task, a new planning approach, named DOF-Decoupled Active Force Sensing (D-DAFS), is presented for such robotics applications. Specifically, the whole task is divided into a sequence of subtasks, each of them focused on reducing a piece of uncertainty, so that the resolution of the inference model can be increased accordingly. This allows a better allocation of resources, focusing on adopting the most accurate, thus expensive, scheme only when the uncertainty is sufficiently low for on-line calculations. The proposed methodology has been applied to perform a 3-DOF localisation with a Staubli RX90 robot, and a series of simulations have been run to prove its effectiveness in coping with high initial uncertainty avoiding computational overheads. %This paper presents the results of the experiment with thirty adult subjects, provides a novel specification for active sensing (i.e., the "DOF decoupling" approach), and illustrates the effectiveness of the method through the results obtained both in simulation and with a Staubli RX90 robot.status: publishe

Optimal docking pose and tactile hook-localisation strategy for AUV intervention: The DIFIS deployment case

The DIFIS project has proposed a new solution for the immediate intervention directly on tanker wrecks so as to contain any leakages and prevent eventual pollution. The method could be extended also to oil well-blow-out cases such as the recent accident in the Gulf of Mexico. The DIFIS deployment typically requires the use of ROVs and dedicated dynamic-positioning ships that increase the cost significantly and make the operations weather-dependent. Eventual AUV use would result in much more efficient and flexible deployment procedures. The scenario studied here consists of a hook-grasping task that is part of the DIFIS mooring procedure. The overall objective is to automate certain processes enabling the use of AUVs or, at least, enhancing the currently foreseen ROV operations. A two-step method is presented consisting of a genetic algorithm for the determination of the optimum docking pose for the vehicle, and a particle filter algorithm that runs on a later stage for the tactile localisation of the hook. The method proposed is rather generic and can be extended to several steps of the DIFIS Deployment procedure, or even to other AUV intervention missions in a semi-structured environment. Results from the two algorithms are also presented and discussed.JRC.G.7-Digital Citizen Securit