Abstract
Biped robots have not achieved the efficient and harmonious locomotion of the human beings, capable of walking and running on unstructured terrains, with obstacles, holes and slopes. With this in mind, researchers started the development of biomimetic solutions to control the locomotion of biped models. This work presents a new solution of motion control of bipedal robots with adaptable stiffness, by exploring effects of joint stiffness in modulating walking behavior. Further, torque adjustment is achieved through a biomimetic controller that mimics and adjusts the natural dynamics of the robot to the environment. Specifically, the torque adjustment is made using AFOs (adaptive frequency oscillator) to generate the correct equilibrium positions that will be applied to the impedance control that computes the torque of each joint. Results show that the biped model is capable of walking in several types of terrain, including flat terrain, ramps, stairs and flat terrain with obstacles.

Abstract

Abstract
Integration in the world of sport is one way for individuals with disabilities or motor disorders to feel more socially integrated, independent, and confident. Boccia is a Paralympic sport, which is increasingly getting more attention around the world. These facts have contributed to the objectives of this work. Including it in the serious games category enables to develop and rehabilitate the cognitive capabilities. The main focus was BC3 classification athletes (users with limited motor characteristics that require the use of an assistive device-a ramp, in this case). This paper describes a realistic Boccia game simulator adapted for people with disabilities that integrates a set of features that includes real physics and social features. These features can be used to enhance the interest of nonpractitioners of the sport and to improve the training conditions. The official Boccia regulation was added to the design of the simulator. The usability and approximation to the reality of the simulator were tested and validated based on the tests performed and data collected via a survey of users with no motor or psychological disorders. Realism and usability rating was almost excellent, and good results were achieved at the assessment of the game experience.

Abstract
Reinforcement learning algorithms are now more appealing than ever. Recent approaches bring power and tuning simplicity to the everyday work machine. The possibilities are endless, and the idea of automating learning without domain knowledge is quite tempting for many researchers. However, in competitive environments such as the RoboCup 3D Soccer Simulation League, there is a lot to be done regarding humanlike behaviors. Current teams use many mechanical movements to perform basic skills, such as running and dribbling the ball. This paper aims to use the PPO algorithm to optimize those skills, achieving natural gaits without sacrificing performance. We use Simspark to simulate a NAO humanoid robot, using visual and body sensors to control its actuators. Based on our results, we propose an indirect control approach and detailed parameter setups to obtain natural running and dribbling behaviors. The obtained performance is in some cases comparable or better than the top RoboCup teams. However, some skills are not ready to be applied in competitive environments yet, due to instability. This work contributes towards the improvement of RoboCup and some related technical challenges.

Abstract

Abstract