Humanoid robot simulator: a realistic dynamics approach

This paper describes a humanoid robot simulator with realistic dynamics. As simulation is a powerful tool for speeding up the control software development, the suggested accurate simulator allows to accomplish this goal. The simulator, based on the Open Dynamics Engine and GLScene graphics library, provides instant visual feedback and allows the user to test any control strategy without damaging the real robot in the early stages of the development. The proposed simulator also captures some characteristics of the environment that are important and allows to test controllers without access to the real hardware. Experimental results are shown that validate this approach

Realistic behaviour simulation of a humanoid robot

This paper describes a humanoid robot simulator with realistic dynamics. As simulation is a powerful tool for speeding up the control software development, the proposed accurate simulator allows to fulfil this goal. The simulator is based on the Open Dynamics Engine and GLScene graphics library, providing instant visual feedback. User is able to test any control strategy without bringing damage to the real robot in the early stages of the development. The proposed simulator also captures some characteristics of the environment that are important and allows to test controllers without access to the real hardware. Experimental and simulator results are presented in order to validate the proposed simulator

Planning and Control Strategies for Motion and Interaction of the Humanoid Robot COMAN+

Despite the majority of robotic platforms are still confined in controlled environments such as factories, thanks to the ever-increasing level of autonomy and the progress on human-robot interaction, robots are starting to be employed for different operations, expanding their focus from uniquely industrial to more diversified scenarios. Humanoid research seeks to obtain the versatility and dexterity of robots capable of mimicking human motion in any environment. With the aim of operating side-to-side with humans, they should be able to carry out complex tasks without posing a threat during operations. In this regard, locomotion, physical interaction with the environment and safety are three essential skills to develop for a biped. Concerning the higher behavioural level of a humanoid, this thesis addresses both ad-hoc movements generated for specific physical interaction tasks and cyclic movements for locomotion. While belonging to the same category and sharing some of the theoretical obstacles, these actions require different approaches: a general high-level task is composed of specific movements that depend on the environment and the nature of the task itself, while regular locomotion involves the generation of periodic trajectories of the limbs. Separate planning and control architectures targeting these aspects of biped motion are designed and developed both from a theoretical and a practical standpoint, demonstrating their efficacy on the new humanoid robot COMAN+, built at Istituto Italiano di Tecnologia. The problem of interaction has been tackled by mimicking the intrinsic elasticity of human muscles, integrating active compliant controllers. However, while state-of-the-art robots may be endowed with compliant architectures, not many can withstand potential system failures that could compromise the safety of a human interacting with the robot. This thesis proposes an implementation of such low-level controller that guarantees a fail-safe behaviour, removing the threat that a humanoid robot could pose if a system failure occurred

Kinematic and three-dimensional dynamic modeling of a biped robot

To view the final version of this © SAGE publication go here: https://doi.org/10.1177/1464419316645243This article focuses on inverse kinematic formulation and dynamic modeling of the Nao biped robot's lower body, accompanied by verification with the joints' angles as experimental data. Dynamic modeling in two different planes is discussed and joint angles for the given positions, nominal conditions, and trajectory computations are simulated and graphically illustrated. A new approach for development of the inverse dynamics on the aforementioned robot's lower body is proposed in this paper, analytically studied, and compared with MSC Adams for two various scenarios of fixed supporting leg and ground contact implementation

Humanoid gait optimization resorting to an improved simulation model

The simulation of a robot with a high number of joints can easily become unstable. Numerical errors on the first joint of the chain are propagated to the other joints. This is a very common problem in humanoid robots. A way to plan the gait for those robots is using simulation and optimization techniques. This paper addresses a new approach to optimize gait parameter sets using an Adaptive Simulated Annealing optimization algorithm combined with a new joint model that reduces its instability. The new model and the optimization are implemented in SimTwo (a developed physical robot simulator that is capable of simulating user defined robots in a three-dimensional space since it includes a physical model based on rigid body dynamics) and results are shown that validate the approach

Fast biped walking with a neuronal controller and physical computation

Biped walking remains a difficult problem and robot models can greatly {facilitate} our understanding of the underlying biomechanical principles as well as their neuronal control. The goal of this study is to specifically demonstrate that stable biped walking can be achieved by combining the physical properties of the walking robot with a small, reflex-based neuronal network, which is governed mainly by local sensor signals. This study shows that human-like gaits emerge without {specific} position or trajectory control and that the walker is able to compensate small disturbances through its own dynamical properties. The reflexive controller used here has the following characteristics, which are different from earlier approaches: (1) Control is mainly local. Hence, it uses only two signals (AEA=Anterior Extreme Angle and GC=Ground Contact) which operate at the inter-joint level. All other signals operate only at single joints. (2) Neither position control nor trajectory tracking control is used. Instead, the approximate nature of the local reflexes on each joint allows the robot mechanics itself (e.g., its passive dynamics) to contribute substantially to the overall gait trajectory computation. (3) The motor control scheme used in the local reflexes of our robot is more straightforward and has more biological plausibility than that of other robots, because the outputs of the motorneurons in our reflexive controller are directly driving the motors of the joints, rather than working as references for position or velocity control. As a consequence, the neural controller and the robot mechanics are closely coupled as a neuro-mechanical system and this study emphasises that dynamically stable biped walking gaits emerge from the coupling between neural computation and physical computation. This is demonstrated by different walking experiments using two real robot as well as by a Poincar\'{e} map analysis applied on a model of the robot in order to assess its stability. In addition, this neuronal control structure allows the use of a policy gradient reinforcement learning algorithm to tune the parameters of the neurons in real-time, during walking. This way the robot can reach a record-breaking walking speed of 3.5 leg-lengths per second after only a few minutes of online learning, which is even comparable to the fastest relative speed of human walking

Biped walking trajectory design and stabilization

Biped robot locomotion has been studied intensively for many decades, and one of the most challenging topics of study is the dynamic motion of the biped robot. This thesis will utilize the zero-moment point (ZMP) along with a simplified dynamics model, the linear inverted pendulum model (LIPM), to design a dynamically stable trajectory for the biped robot, based on given gaits. Two different approaches will be used for the trajectory generation: boundedness constraint and linear-quadratic-regulator method. Both of these methods compute the center of mass (CoM) trajectory for the biped robot. A stabilizer is also designed, and the CoM trajectories are tested using Reem-c robot under the Gazebo simulation environment. Finally, a comprehensive comparison between the two methods will be given