This page has only limited features, please log in for full access.
In large scale systems of embodied agents, such as robot swarms, the ability to flock is essential in many tasks. However, the conditions necessary to artificially evolve self-organised flocking behaviours remain unknown. In this paper, we study and demonstrate how evolutionary techniques can be used to synthesise flocking behaviours, in particular, how fitness functions should be designed to evolve high-performing controllers. We start by considering Reynolds' seminal work on flocking, the boids model, and design three components of a fitness function that are directly based on his three local rules to enforce local separation, cohesion and alignment. Results show that embedding Reynolds' rules in the fitness function can lead to the successful evolution of flocking behaviours. However, only local, fragmented flocking behaviours tend to evolve when fitness scores are based on the individuals' conformity to Reynolds' rules. We therefore modify the components of the fitness function so that they consider the entire group of agents simultaneously, and find that the resulting behaviours lead to global flocking. Furthermore, the results show that alignment need not be explicitly rewarded to successfully evolve flocking. Our study thus represents a significant step towards the use of evolutionary techniques to synthesise collective behaviours for tasks in which embodied agents need to move as a single, cohesive group.
Rita Parada Ramos; Sancho Oliveira; Susana Margarida Vieira; Anders Lyhne Christensen. Evolving flocking in embodied agents based on local and global application of Reynolds’ rules. PLOS ONE 2019, 14, e0224376 .
AMA StyleRita Parada Ramos, Sancho Oliveira, Susana Margarida Vieira, Anders Lyhne Christensen. Evolving flocking in embodied agents based on local and global application of Reynolds’ rules. PLOS ONE. 2019; 14 (10):e0224376.
Chicago/Turabian StyleRita Parada Ramos; Sancho Oliveira; Susana Margarida Vieira; Anders Lyhne Christensen. 2019. "Evolving flocking in embodied agents based on local and global application of Reynolds’ rules." PLOS ONE 14, no. 10: e0224376.
Recent works in evolutionary robotics have shown the viability of evolution driven by behavioural novelty and diversity. These evolutionary approaches have been successfully used to generate repertoires of diverse and high-quality behaviours, instead of driving evolution towards a single, task-specific solution. Having repertoires of behaviours can enable new forms of robotic control, in which high-level controllers continually decide which behaviour to execute. To date, however, only the use of repertoires of open-loop locomotion primitives has been studied. We propose EvoRBC-II, an approach that enables the evolution of repertoires composed of general closed-loop behaviours, that can respond to the robot's sensory inputs. The evolved repertoire is then used as a basis to evolve a transparent higher-level controller that decides when and which behaviours of the repertoire to execute. Relying on experiments in a simulated domain, we show that the evolved repertoires are composed of highly diverse and useful behaviours. The same repertoire contains sufficiently diverse behaviours to solve a wide range of tasks, and the EvoRBC-II approach can yield a performance that is comparable to the standard tabula-rasa evolution. EvoRBC-II enables automatic generation of hierarchical control through a two-step evolutionary process, thus opening doors for the further exploration of the advantages that can be brought by hierarchical control.
Jorge Gomes; Sancho Oliveira; Anders Lyhne Christensen. An approach to evolve and exploit repertoires of general robot behaviours. Swarm and Evolutionary Computation 2018, 43, 265 -283.
AMA StyleJorge Gomes, Sancho Oliveira, Anders Lyhne Christensen. An approach to evolve and exploit repertoires of general robot behaviours. Swarm and Evolutionary Computation. 2018; 43 ():265-283.
Chicago/Turabian StyleJorge Gomes; Sancho Oliveira; Anders Lyhne Christensen. 2018. "An approach to evolve and exploit repertoires of general robot behaviours." Swarm and Evolutionary Computation 43, no. : 265-283.
This paper discusses an emerging field of research in architecture, kinetic design. This approach has been used in different ways through history, but the technological advances of the “Third Industrial Revolution” offer new perspectives on this topic, along with various design innovations. To face this demand, architects must develop new strategies rooted in performance, connectivity and control, and process them to support and inform design. In order to explore these challenges, a group of researchers organized a summer school in 2016. The partnership between ISCTE-IUL and Sapienza University of Rome emerged as an opportunity to join an international community to present recent research, teaching or practice related to architecture, technology, computation, mathematics and geometry. In addition, an experimental learning-by-doing design studio was developed, which allowed for testing a digital workflow to create foldable surfaces based on rigid origami geometry. The major objective of these events, which is summarised in this paper, is to contribute to the debate around digitally-driven kinetic architecture.
Alexandra Paio; Filipa Osório; Sancho Moura Oliveira; Graziano Mario Valenti; Nuno Guimarães. Architecture In-Play, Future Challenges. Nexus Network Journal 2018, 20, 9 -23.
AMA StyleAlexandra Paio, Filipa Osório, Sancho Moura Oliveira, Graziano Mario Valenti, Nuno Guimarães. Architecture In-Play, Future Challenges. Nexus Network Journal. 2018; 20 (1):9-23.
Chicago/Turabian StyleAlexandra Paio; Filipa Osório; Sancho Moura Oliveira; Graziano Mario Valenti; Nuno Guimarães. 2018. "Architecture In-Play, Future Challenges." Nexus Network Journal 20, no. 1: 9-23.
The evolution of task-oriented control for robots with complex locomotor systems is currently out of reach for traditional evolutionary computation techniques, as the coordination of a high number of locomotion parameters in response to the robot’s sensory inputs is extremely challenging. Evolutionary techniques have therefore mainly been applied to the optimization of specific locomotion patterns, such as forward motion. In this paper, we explore the Evolutionary Repertoire-based Control (EvoRBC) approach, which divides the synthesis of control into two steps: (i) the evolution of a repertoire of locomotion primitives using a quality diversity algorithm; and (ii) the evolution of a high-level arbitrator that leverages the locomotion primitives in the repertoire to solve a given task. We comprehensively study the main components of the EvoRBC approach using a four-wheel steering robot. We then conduct a set of experiments in simulation using a hexapod robot. Our results show that EvoRBC is robust to parameter variations, and for all the robots tested, it is able to evolve controllers for a maze navigation task and significantly outperforms the traditional evolutionary robotics approach.
Miguel Duarte; Jorge Gomes; Sancho Oliveira; Anders Lyhne Christensen. Evolution of Repertoire-Based Control for Robots With Complex Locomotor Systems. IEEE Transactions on Evolutionary Computation 2017, 22, 314 -328.
AMA StyleMiguel Duarte, Jorge Gomes, Sancho Oliveira, Anders Lyhne Christensen. Evolution of Repertoire-Based Control for Robots With Complex Locomotor Systems. IEEE Transactions on Evolutionary Computation. 2017; 22 (2):314-328.
Chicago/Turabian StyleMiguel Duarte; Jorge Gomes; Sancho Oliveira; Anders Lyhne Christensen. 2017. "Evolution of Repertoire-Based Control for Robots With Complex Locomotor Systems." IEEE Transactions on Evolutionary Computation 22, no. 2: 314-328.
Catarina Anunciacao Costa Dias Dos Santos; Sancho Moura Oliveira. Databases internationalization model. 2017 12th Iberian Conference on Information Systems and Technologies (CISTI) 2017, 1 .
AMA StyleCatarina Anunciacao Costa Dias Dos Santos, Sancho Moura Oliveira. Databases internationalization model. 2017 12th Iberian Conference on Information Systems and Technologies (CISTI). 2017; ():1.
Chicago/Turabian StyleCatarina Anunciacao Costa Dias Dos Santos; Sancho Moura Oliveira. 2017. "Databases internationalization model." 2017 12th Iberian Conference on Information Systems and Technologies (CISTI) , no. : 1.
Animals have inspired numerous studies on robot locomotion, but the problem of how autonomous robots can learn to take advantage of multimodal locomotion remains largely unexplored. In this paper, we study how a robot with two different means of locomotion can effective learn when to use each one based only on the limited information it can obtain through its onboard sensors. We conduct a series of simulation-based experiments using a task where a wheeled robot capable of jumping has to navigate to a target destination as quickly as possible in environments containing obstacles. We apply evolutionary techniques to synthesize neural controllers for the robot, and we analyze the evolved behaviors. The results show that the robot succeeds in learning when to drive and when to jump. The results also show that, compared with unimodal locomotion, multimodal locomotion allows for simpler and higher performing behaviors to evolve.
Rita Ramos; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. Evolving Controllers for Robots with Multimodal Locomotion. Transactions on Petri Nets and Other Models of Concurrency XV 2016, 340 -351.
AMA StyleRita Ramos, Miguel Duarte, Sancho Oliveira, Anders Lyhne Christensen. Evolving Controllers for Robots with Multimodal Locomotion. Transactions on Petri Nets and Other Models of Concurrency XV. 2016; ():340-351.
Chicago/Turabian StyleRita Ramos; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. 2016. "Evolving Controllers for Robots with Multimodal Locomotion." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 340-351.
We provide a summary of our real-world experiments with a swarm of aquatic surface robots with evolved control. Robotic control was synthesized in simulation, using of- fline evolutionary robotics techniques, and then successfully transferred to a real swarm. Our study presents one of the first demonstrations of evolved control in a swarm robotics system outside of controlled laboratory conditions. Original publication: M. Duarte, V. Costa, J. Gomes, T. Rodrigues, F. Silva, S. M. Oliveira, and A. L. Christensen. Evolution of collective behaviors for a real swarm of aquatic surface robots. PLoS ONE, 11(3):e0151834, 2016.
Miguel Duarte; Vasco Costa; Jorge Gomes; Tiago Rodrigues; Fernando Silva; Sancho Oliveira; Anders Lyhne Christensen. Unleashing the Potential of Evolutionary Swarm Robotics in the Real World. Proceedings of the 2016 on SIGMOD'16 PhD Symposium 2016, 159 -160.
AMA StyleMiguel Duarte, Vasco Costa, Jorge Gomes, Tiago Rodrigues, Fernando Silva, Sancho Oliveira, Anders Lyhne Christensen. Unleashing the Potential of Evolutionary Swarm Robotics in the Real World. Proceedings of the 2016 on SIGMOD'16 PhD Symposium. 2016; ():159-160.
Chicago/Turabian StyleMiguel Duarte; Vasco Costa; Jorge Gomes; Tiago Rodrigues; Fernando Silva; Sancho Oliveira; Anders Lyhne Christensen. 2016. "Unleashing the Potential of Evolutionary Swarm Robotics in the Real World." Proceedings of the 2016 on SIGMOD'16 PhD Symposium , no. : 159-160.
The use of evolutionary robotics in robots with complex means of locomotion has, so far, mainly been limited to gait evolution. Increasing the number of degrees of freedom available to a controller significantly enlarges the search space, which in turn makes the evolution of solutions for a given task more challenging. In this paper, we present Evolutionary Repertoire-based Control (EvoRBC), an approach that enables the evolution of control for robots with arbitrary locomotion complexity. EvoRBC separates the synthesis of control into two levels: the generation of a repertoire of behavior primitives through the application of Quality Diversity techniques; and the evolution of a behavior arbitrator that uses the repertoire's primitives to solve a particular task. We evaluate EvoRBC in simulated robots with different numbers of degrees of freedom in two tasks, navigation and foraging. Our results show that while standard evolutionary approaches are highly affected by the locomotion complexity of the robot, EvoRBC is consistently able to evolve high-performing solutions. We also show that EvoRBC allows for the evolution of general controllers, that can be successfully used in robots different than those with which they were evolved.
Miguel Duarte; Jorge Gomes; Sancho Moura Oliveira; Anders Lyhne Christensen. EvoRBC. Proceedings of the 2016 on SIGMOD'16 PhD Symposium 2016, 93 -100.
AMA StyleMiguel Duarte, Jorge Gomes, Sancho Moura Oliveira, Anders Lyhne Christensen. EvoRBC. Proceedings of the 2016 on SIGMOD'16 PhD Symposium. 2016; ():93-100.
Chicago/Turabian StyleMiguel Duarte; Jorge Gomes; Sancho Moura Oliveira; Anders Lyhne Christensen. 2016. "EvoRBC." Proceedings of the 2016 on SIGMOD'16 PhD Symposium , no. : 93-100.
This paper argues for hands-on, contextual and problem-solving collaborations, that is, for a transdisciplinary approach that establishes direct connections between social and technical disciplines. It is based on our experience as a team of researchers at the Vitruvius Fab Lab (Digital Fabrication Laboratory) of ISCTE-IUL (University Institute of Lisbon, Portugal). The paper presents a particular research and learning initiative–STTF2013 Summer School ‘Sustainable Technologies and Transdisciplinary Futures: From Collaborative Design to Digital Fabrication’, which served as a testbed for our transdisciplinary, critical and open approach. We address its rationale and main challenges, while also discussing recommendations for other transdisciplinary projects striving to integrate social and technical disciplines in research and innovation.
Susana Nascimento; Alexandre Pólvora; Alexandra Paio; Sancho Oliveira; Vasco Rato; Maria João Oliveira; Bárbara Varela; João Pedro Sousa. Sustainable Technologies and Transdisciplinary Futures: From Collaborative Design to Digital Fabrication. Science as Culture 2016, 25, 1 -18.
AMA StyleSusana Nascimento, Alexandre Pólvora, Alexandra Paio, Sancho Oliveira, Vasco Rato, Maria João Oliveira, Bárbara Varela, João Pedro Sousa. Sustainable Technologies and Transdisciplinary Futures: From Collaborative Design to Digital Fabrication. Science as Culture. 2016; 25 (4):1-18.
Chicago/Turabian StyleSusana Nascimento; Alexandre Pólvora; Alexandra Paio; Sancho Oliveira; Vasco Rato; Maria João Oliveira; Bárbara Varela; João Pedro Sousa. 2016. "Sustainable Technologies and Transdisciplinary Futures: From Collaborative Design to Digital Fabrication." Science as Culture 25, no. 4: 1-18.
One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.
Fernando Silva; Miguel Duarte; Luís Correia; Sancho Moura Oliveira; Anders Lyhne Christensen. Open Issues in Evolutionary Robotics. Evolutionary Computation 2016, 24, 205 -236.
AMA StyleFernando Silva, Miguel Duarte, Luís Correia, Sancho Moura Oliveira, Anders Lyhne Christensen. Open Issues in Evolutionary Robotics. Evolutionary Computation. 2016; 24 (2):205-236.
Chicago/Turabian StyleFernando Silva; Miguel Duarte; Luís Correia; Sancho Moura Oliveira; Anders Lyhne Christensen. 2016. "Open Issues in Evolutionary Robotics." Evolutionary Computation 24, no. 2: 205-236.
Control design is one of the prominent challenges in the field of swarm robotics. Evolutionary robotics is a promising approach to the synthesis of self-organized behaviors for robotic swarms but it has, so far, only produced been shown in relatively simple collective behaviors. In this paper, we explore the use of a hybrid control synthesis approach to produce control for a swarm of aquatic surface robots that must perform an intruder detection task. The robots have to go to a predefined area, monitor it, detect and follow intruders, and manage their energy levels by regularly recharging at a base station. The hybrid controllers used in our experiments rely on evolved behavior primitives that are combined through a manually programmed high-level behavior arbitrator. In simulation, we show how simple modifications to the behavior arbitrator can result in different swarm behaviors that use the same underlying behavior primitives, and we show that the composed behaviors are scalable with respect to the swarm size. Finally, we demonstrate the synthesized controller in a real swarm of robots, and show that the behavior successfully transfers from simulation to reality.
Miguel Duarte; Jorge Gomes; Vasco Costa; Sancho Moura Oliveira; Anders Lyhne Christensen. Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task. Transactions on Petri Nets and Other Models of Concurrency XV 2016, 213 -230.
AMA StyleMiguel Duarte, Jorge Gomes, Vasco Costa, Sancho Moura Oliveira, Anders Lyhne Christensen. Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task. Transactions on Petri Nets and Other Models of Concurrency XV. 2016; ():213-230.
Chicago/Turabian StyleMiguel Duarte; Jorge Gomes; Vasco Costa; Sancho Moura Oliveira; Anders Lyhne Christensen. 2016. "Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 213-230.
Swarm robotics is a promising approach characterized by large numbers of relatively small and inexpensive robots. Since such systems typically rely on decentralized control and local communication, they exhibit a number of interesting and useful properties, namely scalability, robustness to individual faults, and flexibility. In this paper, we detail the design and development process of a swarm robotics platform composed of autonomous surface robots, which was designed in order to study the use of robotic swarms in real-world environments. Our aquatic surface robots where manufactured using digital fabrication techniques, such as 3D printing and CNC milling, and all hardware and software has been made available as open-source, thus allowing third-parties to customize and further improve our platform.
Vasco Costa; Miguel Duarte; Tiago Rodrigues; Sancho Moura Oliveira; Anders Lyhne Christensen. Design and development of an inexpensive aquatic swarm robotics system. OCEANS 2016 - Shanghai 2016, 1 -7.
AMA StyleVasco Costa, Miguel Duarte, Tiago Rodrigues, Sancho Moura Oliveira, Anders Lyhne Christensen. Design and development of an inexpensive aquatic swarm robotics system. OCEANS 2016 - Shanghai. 2016; ():1-7.
Chicago/Turabian StyleVasco Costa; Miguel Duarte; Tiago Rodrigues; Sancho Moura Oliveira; Anders Lyhne Christensen. 2016. "Design and development of an inexpensive aquatic swarm robotics system." OCEANS 2016 - Shanghai , no. : 1-7.
Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.
Miguel Duarte; Vasco Costa; Jorge Gomes; Tiago Rodrigues; Fernando Silva; Sancho Oliveira; Anders Lyhne Christensen. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots. PLOS ONE 2016, 11, e0151834 .
AMA StyleMiguel Duarte, Vasco Costa, Jorge Gomes, Tiago Rodrigues, Fernando Silva, Sancho Oliveira, Anders Lyhne Christensen. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots. PLOS ONE. 2016; 11 (3):e0151834.
Chicago/Turabian StyleMiguel Duarte; Vasco Costa; Jorge Gomes; Tiago Rodrigues; Fernando Silva; Sancho Oliveira; Anders Lyhne Christensen. 2016. "Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots." PLOS ONE 11, no. 3: e0151834.
Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and benefit swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.
Pedro Romano; Luís Nunes; Anders Lyhne Christensen; Miguel Duarte; Sancho Moura Oliveira. Genome Variations. Advances in Intelligent Systems and Computing 2015, 309 -319.
AMA StylePedro Romano, Luís Nunes, Anders Lyhne Christensen, Miguel Duarte, Sancho Moura Oliveira. Genome Variations. Advances in Intelligent Systems and Computing. 2015; ():309-319.
Chicago/Turabian StylePedro Romano; Luís Nunes; Anders Lyhne Christensen; Miguel Duarte; Sancho Moura Oliveira. 2015. "Genome Variations." Advances in Intelligent Systems and Computing , no. : 309-319.
In this paper, we discuss wireless sensor and networking technologies for swarms of inexpensive aquatic surface drones in the context of the HANCAD project. The goal is to enable the swarm to perform maritime tasks such as sea-border patrolling and environmental monitoring, while keeping the cost of each drone low. Communication between drones is essential for the success of the project. Preliminary experiments show that XBee modules are promising for energy efficient multi-hop drone-to-drone communication.
Fernando José Da Silva Velez; Aleksandra Nadziejko; Anders Lyhne Christensen; Sancho Oliveira; Tiago Rodrigues; Vasco Costa; Miguel Duarte; Fernando Silva; Jorge Gomes. Wireless Sensor and Networking Technologies for Swarms of Aquatic Surface Drones. 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall) 2015, 1 -2.
AMA StyleFernando José Da Silva Velez, Aleksandra Nadziejko, Anders Lyhne Christensen, Sancho Oliveira, Tiago Rodrigues, Vasco Costa, Miguel Duarte, Fernando Silva, Jorge Gomes. Wireless Sensor and Networking Technologies for Swarms of Aquatic Surface Drones. 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall). 2015; ():1-2.
Chicago/Turabian StyleFernando José Da Silva Velez; Aleksandra Nadziejko; Anders Lyhne Christensen; Sancho Oliveira; Tiago Rodrigues; Vasco Costa; Miguel Duarte; Fernando Silva; Jorge Gomes. 2015. "Wireless Sensor and Networking Technologies for Swarms of Aquatic Surface Drones." 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall) , no. : 1-2.
Anders Lyhne Christensen; Sancho Oliveira; Octavian Postolache; Maria João De Oliveira; Susana Sargento; Pedro Santana; Luís Nunes; Fernando Vélez; Pedro Sebastiao; Vasco Costa; Miguel Duarte; Jorge Gomes; Tiago Rodrigues; Fernando Silva. Design of Communication and Control for Swarms of Aquatic Surface Drones. Proceedings of the International Conference on Agents and Artificial Intelligence 2015, 548 -555.
AMA StyleAnders Lyhne Christensen, Sancho Oliveira, Octavian Postolache, Maria João De Oliveira, Susana Sargento, Pedro Santana, Luís Nunes, Fernando Vélez, Pedro Sebastiao, Vasco Costa, Miguel Duarte, Jorge Gomes, Tiago Rodrigues, Fernando Silva. Design of Communication and Control for Swarms of Aquatic Surface Drones. Proceedings of the International Conference on Agents and Artificial Intelligence. 2015; ():548-555.
Chicago/Turabian StyleAnders Lyhne Christensen; Sancho Oliveira; Octavian Postolache; Maria João De Oliveira; Susana Sargento; Pedro Santana; Luís Nunes; Fernando Vélez; Pedro Sebastiao; Vasco Costa; Miguel Duarte; Jorge Gomes; Tiago Rodrigues; Fernando Silva. 2015. "Design of Communication and Control for Swarms of Aquatic Surface Drones." Proceedings of the International Conference on Agents and Artificial Intelligence , no. : 548-555.
Tiago Rodrigues; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. Beyond Onboard Sensors in Robotic Swarms - Local Collective Sensing through Situated Communication. Proceedings of the International Conference on Agents and Artificial Intelligence 2015, 111 -118.
AMA StyleTiago Rodrigues, Miguel Duarte, Sancho Oliveira, Anders Lyhne Christensen. Beyond Onboard Sensors in Robotic Swarms - Local Collective Sensing through Situated Communication. Proceedings of the International Conference on Agents and Artificial Intelligence. 2015; ():111-118.
Chicago/Turabian StyleTiago Rodrigues; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. 2015. "Beyond Onboard Sensors in Robotic Swarms - Local Collective Sensing through Situated Communication." Proceedings of the International Conference on Agents and Artificial Intelligence , no. : 111-118.
Tiago Rodrigues; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. What You Choose to See Is What You Get: An Experiment with Learnt Sensory Modulation in a Robotic Foraging Task. Computer Vision 2014, 789 -801.
AMA StyleTiago Rodrigues, Miguel Duarte, Sancho Oliveira, Anders Lyhne Christensen. What You Choose to See Is What You Get: An Experiment with Learnt Sensory Modulation in a Robotic Foraging Task. Computer Vision. 2014; ():789-801.
Chicago/Turabian StyleTiago Rodrigues; Miguel Duarte; Sancho Oliveira; Anders Lyhne Christensen. 2014. "What You Choose to See Is What You Get: An Experiment with Learnt Sensory Modulation in a Robotic Foraging Task." Computer Vision , no. : 789-801.
We propose an approach to the synthesis of hierarchical control systems comprising both evolved and manually programmed control for autonomous robots. We recursively divide the goal task into sub-tasks until a solution can be evolved or until a solution can easily be programmed by hand. Hierarchical composition of behavior allows us to overcome the fundamental challenges that typically prevent evolutionary robotics from being applied to complex tasks: bootstrapping the evolutionary process, avoiding deception, and successfully transferring control evolved in simulation to real robotic hardware. We demonstrate the proposed approach by synthesizing control systems for two tasks whose complexity is beyond state of the art in evolutionary robotics. The first task is a rescue task in which all behaviors are evolved. The second task is a cleaning task in which evolved behaviors are combined with a manually programmed behavior that enables the robot to open doors in the environment. We demonstrate incremental transfer of evolved control from simulation to real robotic hardware, and we show how our approach allows for the reuse of behaviors in different tasks.
Miguel Duarte; Sancho Moura Oliveira; Anders Lyhne Christensen. Evolution of Hybrid Robotic Controllers for Complex Tasks. Journal of Intelligent & Robotic Systems 2014, 78, 463 -484.
AMA StyleMiguel Duarte, Sancho Moura Oliveira, Anders Lyhne Christensen. Evolution of Hybrid Robotic Controllers for Complex Tasks. Journal of Intelligent & Robotic Systems. 2014; 78 (3-4):463-484.
Chicago/Turabian StyleMiguel Duarte; Sancho Moura Oliveira; Anders Lyhne Christensen. 2014. "Evolution of Hybrid Robotic Controllers for Complex Tasks." Journal of Intelligent & Robotic Systems 78, no. 3-4: 463-484.
Miguel Duarte; Sancho Oliveira; Anders Christensen. Hybrid Control for Large Swarms of Aquatic Drones. Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems 2014, 1 .
AMA StyleMiguel Duarte, Sancho Oliveira, Anders Christensen. Hybrid Control for Large Swarms of Aquatic Drones. Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems. 2014; ():1.
Chicago/Turabian StyleMiguel Duarte; Sancho Oliveira; Anders Christensen. 2014. "Hybrid Control for Large Swarms of Aquatic Drones." Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems , no. : 1.