Combined Controllers that Follow Imperfect Input Motions for Humanoid Robots

Humanoid robots have the potential to become a part of everyday life as their hardware and software challenges are being solved. In this paper we present a system that gets as input a motion trajectory in the form of motion capture data, and produces a controller that controls a humanoid robot in real-time to achieve a motion trajectory that is similar to the input motion data. The controller expects the input motion data not to be dynamically feasible for the robot and employs a combined controller with corrective components to keep the robot balanced while following the motion. Since the system can run in real-time, it can be thought of a candidate for teleoperation of humanoid robots using motion capture hardware

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

Biped walking control design based on zero moment point dynamics

Biped walking control for humanoid robots has been a challenging yet promising research topic in the past decades. The complicated nonlinear dynamics and numerous degrees of freedom are the main obstacles for biped walking control. This thesis studies the complete control scheme of biped walking control based on Zero Moment Point dynamics. Starting with basic de nitions, a new trajectory planning method using boundedness solutions of Linear Inverted Pendulum Model is studied and implemented as a replanning algorithm. Stabilizers for walking trajectory tracking are investigated and evaluated, with an emphasis on the Whole Body Cooperation method, which is then implemented along with the replanning algorithm in simulations