| 1. |
- Aguzzi, Jacopo, et al.
(författare)
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Developing technological synergies between deep-sea and space research
- 2022
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Ingår i: Elementa. - 2325-1026. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Recent advances in robotic design, autonomy and sensor integration create solutions for the exploration of deep-sea environments, transferable to the oceans of icy moons. Marine platforms do not yet have the mission autonomy capacity of their space counterparts (e.g., the state of the art Mars Perseverance rover mission), although different levels of autonomous navigation and mapping, as well as sampling, are an extant capability. In this setting their increasingly biomimicked designs may allow access to complex environmental scenarios, with novel, highly-integrated life-detecting, oceanographic and geochemical sensor packages. Here, we lay an outlook for the upcoming advances in deep-sea robotics through synergies with space technologies within three major research areas: biomimetic structure and propulsion (including power storage and generation), artificial intelligence and cooperative networks, and life-detecting instrument design. New morphological and material designs, with miniaturized and more diffuse sensor packages, will advance robotic sensing systems. Artificial intelligence algorithms controlling navigation and communications will allow the further development of the behavioral biomimicking by cooperating networks. Solutions will have to be tested within infrastructural networks of cabled observatories, neutrino telescopes, and off-shore industry sites with agendas and modalities that are beyond the scope of our work, but could draw inspiration on the proposed examples for the operational combination of fixed and mobile platforms.
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| 2. |
- Ferri, Gabriele, et al.
(författare)
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DustCart, a Mobile Robot for Urban Environments : Experiments of Pollution Monitoring and Mapping during Autonomous Navigation in Urban Scenarios
- 2010
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Ingår i: Proceedings of ICRA Workshop on Networked and Mobile Robot Olfaction in Natural, Dynamic Environments.
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Konferensbidrag (refereegranskat)abstract
- In the framework of DustBot European project, aimed at developing a new multi-robot system for urban hygiene management, we have developed a twowheeled robot: DustCart. DustCart aims at providing a solution to door-to-door garbage collection: the robot, called by a user, navigates autonomously to his/her house; collects the garbage from the user and discharges it in an apposite area. An additional feature of DustCart is the capability to monitor the air pollution by means of an on board Air Monitoring Module (AMM). The AMM integrates sensors to monitor several atmospheric pollutants, such as carbon monoxide (CO), particular matter (PM10), nitrogen dioxide (NO2), ozone (O3) plus temperature (T) and relative humidity (rHu). An Ambient Intelligence platform (AmI) manages the robots’ operations through a wireless connection. AmI is able to collect measurements taken by different robots and to process them to create a pollution distribution map. In this paper we describe the DustCart robot system, focusing on the AMM and on the process of creating the pollutant distribution maps. We report results of experiments of one DustCart robot moving in urban scenarios and producing gas distribution maps using the Kernel DM+V algorithm. These experiments can be considered as one of the first attempts to use robots as mobile monitoring devices that can complement the traditional fixed stations.
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| 3. |
- Laschi, Cecilia, et al.
(författare)
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A Bio-inspired Neural Sensory-Motor Coordination Scheme for Robot Reaching and Preshaping
- 2006
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Ingår i: Proceedings of the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics : BioRob 2006. - Piscataway, NJ : IEEE. - 1424400406 ; , s. 531-536
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach for and to grasp an object, while pre-shaping the fingers to the required grasp configuration. A model for sensory-motor coordination derived from studies in humans inspired the development of the scheme. A special feature of this model is the prediction of the tactile image perceived after grasping. The proposed scheme is based on a neuro-fuzzy modnle that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for grasping, selects the best-suited hand configuration, and predicts the tactile feedback after grasping. The implementation of the scheme on a humanoid robot ailowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.
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| 4. |
- Laschi, Cecilia, et al.
(författare)
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Bio-inspired sensory-motor coordination
- 2008
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Ingår i: Autonomous Robots. - : Springer. - 0929-5593 .- 1573-7527. ; 25:1-2, s. 1-2
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Tidskriftsartikel (refereegranskat)
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| 5. |
- Pinpin, Lord Kenneth, et al.
(författare)
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Utilizing gaze behavior for inferring task transitions using abstract hidden markov models
- 2016
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Ingår i: Inteligencia Artificial. Ibero-American Journal of Artificial Intelligence. - : IBERAMIA: Sociedad Iberoamericana de Inteligencia Artificial. - 1137-3601 .- 1988-3064. ; 19:58, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations.
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