Search results for " robotics."
showing 10 items of 113 documents
Artificial Pleasure and Pain Antagonism Mechanism in a Social Robot
2017
The goal of the work is to build some Python modules that allow the Nao robot to emulate a somatosensorial system similar to the human one. Assuming it can perceive some feelings similar to the ones recognized by the human system, it will be possible to make it react appropriately to the external stimuli. The idea is to have a group of software sensors working simultaneously, providing some feedback to show how the robot is feeling at a particular time. It will be able to feel articular pain and stress, to perceive people in his surroundings (and in a future work to react according to the knowledge of them with face recognition), feel pleasure by recognizing caresses on his head and respond…
Creation and cognition for humanoid live dancing
2016
Abstract Computational creativity in dancing is a recent and challenging research field in Artificial Intelligence and Robotics. We present a cognitive architecture embodied in a humanoid robot capable to create and perform dances driven by the perception of music. The humanoid robot is able to suitably move, to react to human mate dancers and to generate novel and appropriate sequences of movements. The approach is based on a cognitive architecture that integrates Hidden Markov Models and Genetic Algorithms. The system has been implemented on a NAO robot and tested in public setting-up live performances, obtaining positive feedbacks from the audience.
A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning
2016
Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…
Categories, Quantum Computing, and Swarm Robotics: A Case Study
2022
The swarms of robots are examples of artificial collective intelligence, with simple individual autonomous behavior and emerging swarm effect to accomplish even complex tasks. Modeling approaches for robotic swarm development is one of the main challenges in this field of research. Here, we present a robot-instantiated theoretical framework and a quantitative worked-out example. Aiming to build up a general model, we first sketch a diagrammatic classification of swarms relating ideal swarms to existing implementations, inspired by category theory. Then, we propose a matrix representation to relate local and global behaviors in a swarm, with diagonal sub-matrices describing individual featur…
A Cognitive Framework for Imitation Learning
2006
Abstract In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how this Conceptual Area can be employed to efficiently organize perceptual data, to learn movement primitives from human demonstration and to generate complex actions by combining and sequencing simpler ones. The proposed architecture ha…
Anchoring symbols to conceptual spaces: the case of dynamic scenarios.
2003
In recent years, there have been several proposals for the realization of models inspired to biological solutions for pattern recognition. In this work we propose a new approach, based on a hierarchical modular structure, to realize a system capable to learn by examples and recognize objects in digital images. The adopted techniques are based on multiresolution image analysis and neural networks. Performance on two different data sets and experimental timings on a single instruction multiple data (SIMD) machine are also reported.
A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm
2022
Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with unce…
The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot†
2022
The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from a control standpoint, the accurate identification of push-points and reliable determination of feasible contact reaction forces are required. This is difficult to achieve with rigidly actuated robots because of the lack of compliance. As a possible solution to this challenge, our research group recently presented Serpens, a low-cost, open-source, and highly compliant multi-purpose modular…
Design and Characterization of a Miniature Hydraulic Power Supply for High-Bandwidth Control of Soft Robotics
2020
Soft robotics holds enormous promise for a wide class of applications. However, system controllability, bandwidth, portability, and energy efficiency of soft robot power supplies are often inadequate. Soft robotics desperately needs improved solutions to drive soft actuators either pneumatically or hydraulically. This research paper offers a contribution to bridge this gap. It deals with small-scale power supplies for hydraulically-driven soft robots based on fluidic elastomer actuators in the power range 5-400 W. A design procedure for such power supplies is developed with an emphasis on high-bandwidth control. The performance requirements are established based on a literature survey, and …
Teaching Physics Concepts Using Educational Robotics
2019
This paper reports a study included in the national project PROMISE funded by the Italian Ministry of Education, University and Research. It examines the application of an educational robotics laboratory with secondary school students for learning concept about physics. In the paper we describe the didactic strategies that have been implemented during the activities and we give some qualitative outcomes related to effectiveness of the laboratory. Indeed we observed interesting results in students both in term of learning and of interest and participation. The importance of teacher involvement in this type of intervention will also be discussed.