Source: http://lima.sist.shanghaitech.edu.cn/
Timestamp: 2019-04-19 19:09:22+00:00

Document:
We combine Machine Learning and robots to allow them to adapt to malfunctions and disturbances from the world we live in!
The presence of robots in our lives increases gradually, and advances from Machine Learning and AI are usually applied to vision, audio and data mining. We believe that physical machines can also profit from this "intelligence" and better adapt to sources of noise/disturbance within our reality. Our applications range from optimization of industrial manipulators to the cooperative/competitive learning of robots while performing tasks.
In an industrial environment the capacity to adapt to malfunctions and noises can save hours of a halted production line.
Although models are helpful, robots must learn how to exist in our environment by interacting with it.
Legs and wheels have different benefits and shortfalls. Why choose sides? We work with both! J. of Royal Society 2018 paper!
Experiments with robots require time. Bayesian methods combine prior model to newly acquired data to reach faster learning rates. PLoS 2017 paper!
Ms. Li, Shuting - Visiting student - Sichuan U.
Ms. Rong, Chunyan - Visiting student - Jinan U.
Liu, X. ; ROSENDO, A. ; Ikemoto, S. ; Shimizu, M. ; Hosoda, K.. Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping, Journal of the Royal Society Interface(IF=3.58), vol. 15, no 140, 2018.
ROSENDO, A. ; von Atzigen, M. ; Iida, F.. The trade-off between morphology and control in the co-optimized design of robots, PLoS ONE(IF= 2.81), vol. 12, no 10, e0186107, 2017.
Vujovic, V. ; ROSENDO, A. ; Brodbeck, L. ; Iida, F.. Evolutionary developmental robotics: Improving locomotion of physical robots. Artificial Life (IF= 1.96), v. 23, no 2, 2017.
Hughes, J. ; Culha, U. ; Giardina, F. ; Guenther, F. ; ROSENDO, A. ; Iida, F.. Soft manipulators and grippers: A review. Frontiers of Robotics and AI, v. 3, p. 1-12, 2016.
Iida, F. ; ROSENDO, A. ; Nurzaman, S. ; Laschi, C. ; Wood, R.; Floreano, D.. Soft robotics and morphological computation. IEEE Robotics and Automation Magazine (IF = 1.82), v. 23, p. 28-29, 2016.
ROSENDO, A. ; Giardina, F. ; Hughes, J. ; Iida, F.. Soft solutions for hard problems. IEEE Robotics and Automation Magazine (IF = 1.82), v. 23, p. 125-127, 2016.
ROSENDO, A. ; Iida, F.. Energy efficient hopping with Hill-type muscle properties on segmented legs. Bioinspiration and Biomimetics (IF = 2.35), v. 11, p. 036002, 2016.
Hunt, J. ; Giardina, F. ; ROSENDO, A. ; Iida, F.. Improving efficiency for an open-loop controlled locomotion with a pulsed actuation. IEEE Transactions on Mechatronics (IF = 4.35), v. 21, p. 1581-1591, 2016.
ROSENDO, A. ; Liu, X. ; Shimizu, M ; Hosoda, K.. Stretch reflex improves rolling stability during hopping of a decerebrate system. Bioinspiration and Biomimetics (IF = 2.35), v. 10, p. 016008, 2015.
ROSENDO, A. ; Nakatsu, S. ; Narioka, K. ; Hosoda, K. . Producing alternating gait on uncoupled feline hindlimbs: muscular unloading rule on a biomimetic robot. Advanced Robotics (IF = 0.92), v. 28, p. 351-365, 2014.
ROSENDO, A.; Houseago, C. ; Iida, F. . Lessons on the reality gap: Iterations between virtual and real robots, Intl. Conf. on Artificial Life and Robotics, ICAROB 2018, Oita, Japan.
Saar, K.A. ; ROSENDO, A.; Iida, F. . Bayesian Optimization of gaits on a bipedal SLIP model, IEEE Intl. Conf. on Robotics and Biomimetics, IEEE ROBIO 2017, Macao.
Jones, G. ; ROSENDO, A.; Stopforth, R. . Prosthetic design directives: Low-cost hands within reach. IEEE Intl. Conf. on Rehabilitation Robotics, IEEE ICORR 2017, London, UK.
Mangezi, A. ; ROSENDO, A.; Howard, M. ; Stopforth, R.. Embroidered Archimedean Spiral EMG Electrodes for Prosthetic Control. IEEE Intl. Conf. on Rehabilitaiton Robotics, IEEE ICORR 2017, London, UK.
Liu, X. ; ROSENDO, A. ; Ikemoto, S. ; Hosoda, K.. Higher Jumping of a Biped Musculoskeletal Robot with Foot Windlass Mechanism. The 14th Intl. Conf. on Intelligent Autonomous Systems, IAS 2016, Shanghai, China.

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