Pedro Neto

University of Coimbra | UC · Department of Mechanical Engineering

Continuous gesture spotting is a major topic in human-robot interaction (HRI) research. Human gestures are captured by sensors that provide large amounts of data that can be redundant or incomplete, correlated or uncorrelated. Data dimensionality reduction (DDR) techniques allow to represent such data in a low-dimensional space, making the classifi...

Continuous and real-time gesture spotting is a key factor in the development of novel human-machine interaction (HMI) modalities. Gesture recognition can be greatly improved with previous reliable segmentation. This paper introduces a new unsupervised threshold-based hand/arm gesture segmenta-tion method to accurately divide continuous data streams...

New and more natural human-robot interfaces are of crucial interest to the evolution of robotics. This paper addresses continuous and real-time hand gesture spotting, i.e., gesture segmentation plus gesture recognition. Gesture patterns are recognized by using artificial neural networks (ANNs) specifically adapted to the process of controlling an i...

In the quest for electrically-driven soft actuators, the focus has shifted away from liquid-gas phase transition, commonly associated with reduced strain rates and actuation delays, in favour of electrostatic and other electrothermal actuation methods. This prevented the technology from capitalizing on its unique characteristics, particularly: low...

Collaborative robots are increasingly popular for assisting humans at work and daily tasks. However, designing and setting up interfaces for human-robot collaboration is challenging, requiring the integration of multiple components, from perception and robot task control to the hardware itself. Frequently, this leads to highly customized solutions...

Bio-inspired soft robots have already shown the ability to handle uncertainty and adapt to unstructured environments. However, their availability is partially restricted by time-consuming, costly and highly supervised design-fabrication processes, often based on resource intensive iterative workflows. Here, we propose an integrated approach targeti...

Bio-inspired soft robots have already shown the ability to handle uncertainty and adapt to unstructured environments. However, their availability is partially restricted by time-consuming, costly, and highly supervised design-fabrication processes, often based on resource-intensive iterative workflows. Here, we propose an integrated approach target...

Real-time robot actuation is one of the main challenges to overcome in human-robot interaction. Most visual sensors are either too slow or their data are too complex to provide meaningful information and low latency input to a robotic system. Data output of an event camera is high-frequency and extremely lightweight, with only 8 bytes per event. To...

Robots have been successfully deployed in both traditional and novel manufacturing processes. However, they are still difficult to program by non-experts, which limits their accessibility to a wider range of potential users. Programming robots requires expertise in both robotics and the specific manufacturing process in which they are applied. Robo...

The featured dataset, the Event-based Dataset of Assembly Tasks (EDAT24), showcases a selection of manufacturing primitive tasks (idle, pick, place, and screw), which are basic actions performed by human operators in any manufacturing assembly. The data were captured using a DAVIS240C event camera, an asynchronous vision sensor that registers event...

Robots have been successfully deployed in both traditional and novel manufacturing processes. However, they are still difficult to program by non-experts, which limits their accessibility to a wider range of potential users. Programming robots requires expertise in both robotics and the specific manufacturing process in which they are applied. Robo...

The featured dataset, the Event-based Dataset of Assembly Tasks (EDAT24), showcases a selection of manufacturing primitive tasks (idle, pick, place, and screw), which are basic actions performed by human operators in any manufacturing assembly. The data were captured using a DAVIS240C event camera, an asynchronous vision sensor that registers event...

Machines that mimic humans have inspired scientists for centuries. Bioinspired soft robotic hands are a good example of such an endeavor, featuring intrinsic material compliance and continuous motion to deal with uncertainty and adapt to unstructured environments. Recent research led to impactful achievements in functional designs, modeling, fabric...

Machines that mimic humans have inspired scientists for centuries. Bio-inspired soft robotic hands are a good example of such an endeavor, featuring intrinsic material compliance and continuous motion to deal with uncertainty and adapt to unstructured environments. Recent research led to impactful achievements in functional designs, modeling, fabri...

Robots are increasingly present in our lives, sharing the workspace and tasks with human co-workers. However, existing interfaces for human-robot interaction / cooperation (HRI/C) have limited levels of intuitiveness to use and safety is a major concern when humans and robots share the same workspace. Many times, this is due to the lack of a reliab...

The development of machine learning algorithms has been gathering relevance to address the increasing modelling complexity of manufacturing decision-making problems. Reinforcement learning is a methodology with great potential due to the reduced need for previous training data, i.e., the system learns along time with actual operation. This study fo...

Application of soft and compliant joints in grasping mechanisms received an increasing attention during recent years. This article suggests the design and development of a novel bio-inspired compliant finger which is composed of a 3D printed rigid endoskeleton covered by a soft matter. The overall integrated system resembles a biological structure...

Deep reinforcement learning (DRL) has demonstrated its potential in solving complex manufacturing decision-making problems, especially in a context where the system learns over time with actual operation in the absence of training data. One interesting and challenging application for such methods is the assembly sequence planning (ASP) problem. In...

This paper proposes a novel method for human hands tracking using data from an event camera. The event camera detects changes in brightness, measuring motion, with low latency, no motion blur, low power consumption and high dynamic range. Captured frames are analysed using lightweight algorithms reporting 3D hand position data. The chosen pick-and-...

We propose a novel way of solving the issue of classification of out-of-vocabulary gestures using Artificial Neural Networks (ANNs) trained in the Generative Adversarial Network (GAN) framework. A generative model augments the data set in an online fashion with new samples and stochastic target vectors, while a discriminative model determines the c...

Online recognition of gestures is critical for intuitive human-robot interaction (HRI) and further push collaborative robotics into the market, making robots accessible to more people. The problem is that it is difficult to achieve accurate gesture recognition in real unstructured environments, often using distorted and incomplete multisensory data...

Force and proximity sensors are key in robotics, especially when applied in collaborative robots that interact physically or cognitively with humans in real unstructured environments. However, most existing sensors for use in robotics are limited by: 1) their scope, measuring single parameters/events and often requiring multiple types of sensors, 2...

Robotics and intelligent systems are intricately connected, each exploring their respective capabilities and moving towards a common goal [...]

Robotic systems are key in industry 4.0 context. While there are many robot models available in the market, the number of grippers with sensing capabilities at an affordable cost is reduced. Traditional robot grippers are targeted to perform specific tasks, with unchangeable configurations and limited ability to adapt to different working scenarios...

Collaborative robots are growing exponentially, with applications in the most diverse domains and operating side by side with humans in unstructured and changing environments. Such a scenario requires robot programmers to develop complex applications, integrating Artificial Intelligence (AI), sensing and control, both rapidly and efficiently. Pytho...

There is an increasing demand for low-cost and lightweight robot manipulators to operate in the most diverse domains. In the last few years, in parallel with additive manufacturing advancement, we witness the emergence of innovative robot designs fabricated using 3D printing. However, the development of a functional robot is still a complex process...

There is a great demand for the robotization of manufacturing processes featuring monotonous labor. Some manufacturing tasks requiring specific skills (welding, painting, etc.) suffer from a lack of workers. Robots have been used in these tasks, but their flexibility is limited since they are still difficult to program/re-program by non-experts, ma...

Robotics and intelligent systems are key technologies to promote efficient and innovative applications in the most diverse domains (industry, healthcare, agriculture, construction, mobility, etc [...]

There is a great demand for the robotization of manufacturing processes fea-turing monotonous labor. Some manufacturing tasks requiring specific skills (welding, painting, etc.) suffer from a lack of workers. Robots have been used in these tasks, but their flexibility is limited since they are still difficult to program/re-program by non-experts, m...

Additive manufacturing (AM) is revolutionizing industry, allowing to prototype and fabricate custom-made parts with complex geometries rapidly and at an affordable cost. The use of robots to perform AM has great potentials due to its flexibility and ability to produce multi-directional fabrication paths, conducting to the production of parts that a...

Deep reinforcement learning (DRL) has demonstrated its potential in solving complex manufacturing decision-making problems, especially in a context where the system learns over time with actual operation in the absence of training data. One interesting and challenging application for such methods is the assembly sequence planning (ASP) problem. In...

Hand-guiding is a key feature of collaborative robots, allowing unskilled users to interact with them in an intuitive manner. This physical interface is extensively used for robot positioning during the human–robot interactive process. However, end-effector (EEF) precise and smooth positioning is still difficult to achieve by hand-guiding. This stu...

Force and proximity sensors are key in robotics, especially when applied in collaborative robots that interact physically or cognitively with humans in real unstructured environments. However, most existing sensors for use in robotics are limited by: 1) their scope, measuring single parameters/events and often requiring multiple types of sensors, 2...

Purpose This paper proposes a novel method for human hands tracking using data from an event camera. The event camera detects changes in brightness, measuring motion, with low latency, no motion blur, low power consumption and high dynamic range. Captured frames are analysed using lightweight algorithms reporting three-dimensional (3D) hand positio...

Edition of the Proceedings of the 2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC 2021)

In this work, a novel optimisation-simulation based on the Recursive Optimisation-Simulation Approach (ROSA) methodology is developed to provide effective decision-support for integrated production planning and scheduling. The proposed iterative approach optimises production plans while satisfying complex scheduling constraints, such as robots' all...

The development of machine learning algorithms has been gathering relevance to address the increasing modelling complexity of manufacturing decision-making problems. Reinforcement learning is a methodology with great potential due to the reduced need for previous training data, i.e. the system learns along time with actual operation. This study foc...

Redundancy in robotic manipulators has many advantages. It is successfully used to achieve better dexterity, to avoid obstacles, singularities or the kinematic limitations. However, redundancy makes the Inverse Kinematics (IK) problem harder to solve. The Damped Least Squares (DLS) is a powerful method for calculating the inverse kinematics of redu...

Robots are increasingly present in our lives, sharing the workspace and tasks with human co-workers. However, existing interfaces for human-robot interaction / cooperation (HRI/C) have limited levels of intuitiveness to use and safety is a major concern when humans and robots share the same workspace. Many times, this is due to the lack of a reliab...

Simulation and model-based design software packages are widely used in many engineering disciplines. When it comes to robotics those tools are very important for robot design, simulation and the development of control algorithms before the implementation on the real robot. Simulink by MathWorks® is an advanced model-based design tool. It is popular...

Collaborative redundant manipulators are becoming more popular in industry. Lately, sensitive variants of those robots are introduced to the market. Their sensitivity is owed to the unique technology of integrating torque sensors into their joints. This technology has been used extensively for collision detection. Nevertheless, it can be used in ot...

This study investigates the application of Newton method to the problems of collision avoidance and path planning for robotic manipulators, especially robots with high Degrees of Freedom (DOF). The proposed algorithm applies to the potential fields method, where the Newton technique is used for performing the optimization. As compared to classical...

Human gesture recognition has assumed a capital role in industrial applications, such as Human-Machine Interaction. We propose an approach for segmentation and classification of dynamic gestures based on a set of handcrafted features, which are drawn from the skeleton data provided by the Kinect sensor. The module for gesture detection relies on a...

Collaborative robotics have a large potential for use in industrial applications. Nevertheless, this potential is currently unrealized and one of the reasons is the challenges in planning and designing while considering the safety requirements of these new types of applications. In this article, we will use an exemplary application to describe the...

Metal Additive Manufacturing (MAM) using Direct Energy Deposition (DED) is a fast-growing technological process that brings a positive boost to manufacturing industry. When compared with traditional manufacturing methods the advantages of DED are multiple, it is more cost-effective, reduces material waste and presents reduced manufacturing lead-tim...

Increasingly, industry is looking to better integrate their industrial processes and related data. Interoperability is key since the organizations need to share data between them, between departments and the different stages of a given technological process. The problem is that many times there are no standard data formats for data exchange between...

In this paper we present a novel strategy and implementation of autonomous navigation for the Pepper robot. The proposed solution is modular and relies on the proper integration of existing Pepper functionalities. The human interacts with the robot using voice and/or gesture commands to setup the robot functionalities. An example use case demonstra...

Hand-guiding of collaborative redundant manipu-lators allows an unskilled user to interact and program the robot intuitively. Many industrial applications require precise positioning at the end-effector (EEF) level inside cluttered environments , where manipulator's redundancy is required. Yet, the potentialities of redundancy while hand-guiding at...

The use of gestures as interface between humans and robots to facilitate communication between them is a long-sought goal. Although many gesture solutions have been presented, none of them cope entirely with wrong gesture recognition. This study proposes a novel electromyography (EMG) prototype sensor to capture gestures and also algorithms and pro...

Human-robot collision avoidance is a key in collaborative robotics and in the framework of Industry 4.0. It plays an important role for achieving safety criteria while having humans and machines working side-by-side in unstructured and time-varying environment. This study introduces the subject of manipulator's on-line collision avoidance into a re...

Christoffel symbols of the first kind are very important in robot dynamics. They are used for tuning various proposed robot controllers, for determining the bounds on Coriolis/Centrifugal matrix, for mathematical formulation of optimal trajectory calculation, among others. In the literature of robot dynamics, Christoffel symbols of the first kind a...

Flexibility, adaptability and standardization of multidisciplinary production processes are key issues for today's industry. The digitalization of industry partially helps to overcome these challenges, leading to the need for efficient management of data. AutomationML has been pointed as a solution to solve the problem of data exchange between hete...

Online gesture classification can rely on unsupervised segmentation in order to divide the data stream into static and dynamic segments for individual classification. However, this process requires motion detection calibration and adds complexity to the classification, thus becoming an additional failure point. An alternative is the sequential (dyn...

Collaborative robots (Cobots) are indispensable tools in the factories of the future. Owing to their safety centered design, Cobots are allowed to work side by side with humans, making their use as an assistive third hand appealing for tedious assembly tasks. Consequently, we propose a robot that can be hand-guided to lift and hold parts in place w...

In the upcoming industrial revolution (Industry 4.0) automation and robotics play a central role. Humans and robots are expected to share the same workspace and work safely side by side. Consequently, various collaborative robots have been introduced to the market. Nevertheless, those robots are still limited in their reactions. In some cases they...

Human–robot collision avoidance is a key in collaborative robotics and in the framework of Industry 4.0. It plays an important role for achieving safety criteria while having humans and machines working side-by-side in unstructured and time-varying environment. This study introduces the subject of manipulator’s on-line collision avoidance into a re...

This study introduces the Geometric Dynamics Algorithm (GDA) for representing the dynamics of serially linked robots. GDA is non-symbolic, preserves simple formulation, and is convenient for numerical implementation. GDA-based algorithms are deduced for efficient calculation of various dynamic quantities including (1) joint space inertia matrix (JS...

We propose a novel way of solving the issue of classification of out-of-vocabulary gestures using Artificial Neural Networks (ANNs) trained in the Generative Adversarial Network (GAN) framework. A generative model augments the data set in an online fashion with new samples and stochastic target vectors, while a discriminative model determines the c...

This paper presents a literature review on pattern recognition of electromyography (EMG) signals and its applications. EMG technology is introduced and the most relevant aspects for the design an EMG-based system are highlighted, including signal acquisition and filtering. EMG-based systems have been used with relative success to control upper-and...

The paradigm for robot usage has changed in the last few years, from a scenario in which robots work isolated to a scenario where robots collaborate with human beings, exploiting and combining the best abilities of robots and humans. The development and acceptance of collaborative robots is highly dependent on reliable and intuitive human-robot int...

In this study we investigate the use of a laser scanner/range-finder and inertial measurement units (IMUs) for the application of human-robot interaction in a dynamic environment with moving obstacles/humans. Humans and robots are represented by capsules, allowing to calculate the human-robot minimum distance on-the-fly. A major challenge is to cap...