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In Evolutionary Robotics (ER), controllers are assessed in a single or a few environments. As a consequence, good performances in new different contexts are not guaranteed. While a lot of ER works deal with robustness, i.e. the ability to perform well on new contexts close to the ones used for evaluation, no current approach is able to promote broader(More)
—The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the physical robot, remains a critical issue in Evolutionary Robotics (ER). We hypothesize that this gap highlights a conflict between the efficiency of the solutions in simulation and their transferability from simulation to reality: the most efficient(More)
The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the real system, remains a critical issue in Evolutionary Robotics (ER); it prevents ER application to real-world problems. We hypothesize that this gap mainly stems from a conflict between the efficiency of the solutions in simulation and their(More)
Damage recovery is critical for autonomous robots that need to operate for a long time without assistance. Most current methods are complex and costly because they require anticipating each potential damage in order to have a contingency plan ready. As an alternative, we introduce the T-resilience algorithm , a new algorithm that allows robots to quickly(More)
— In evolutionary robotics, controllers are often designed in simulation, then transferred onto the real system. Nevertheless, when no accurate model is available, controller transfer from simulation to reality means potential performance loss. It is the reality gap problem. Unmanned aerial vehicles are typical systems where it may arise. Their locomotion(More)
In robotics, gradient-free optimization algorithms (e.g. evolutionary algorithms) are often used only in simulation because they require the evaluation of many candidate solutions. Nevertheless , solutions obtained in simulation often do not work well on the real device. The transferability approach aims at crossing this gap between simulation and reality(More)
Wheel-legged hybrid robots promise to combine the efficiency of wheeled robots with the versatility of legged robots: they are able to roll on simple terrains, to dynamically adapt their posture and even to walk on uneven grounds. Although different locomotion modes of such robots have been studied, a pivotal question remains: how to automatically adapt the(More)
Well-differentiated squamous cell carcinomas were induced in hamster buccal pouch epithelium by twice weekly topical applications of N-methyl-N-benzylnitrosamine (MBN) or 7,12-dimethylbenz[a]anthracene (DMBA) over a period of 15 weeks. Each of the 22 tumors induced (14 MBN and eight DMBA) were evaluated by single-strand conformation polymorphism and DNA(More)
Wheel-legged hybrid robots are versatile machines that can employ several locomotion modes; however, automatically choosing the right locomotion mode is still an open problem in robotics. We here propose that the robot autonomously discovers its locomotion mode using a multi-objective evolutionary optimization and a fixed internal model. Three objectives(More)