ABSTRACT
We extend the quadratic program (QP)-based task-space character control approach-initially intended for individual character animation-to multiple characters interacting among each other or with mobile/articulated elements of the environment. The interactions between the characters can be either physical interactions, such as contacts that can be established or broken at will between them and for which the forces are subjected to Newton's third law, or behavioral interactions, such as collision avoidance and cooperation that naturally emerge to achieve collaborative tasks from high-level specifications. We take a systematic approach integrating all the equations of motions of the characters, objects, and articulated environment parts in a single QP formulation in order to embrace and solve the most general instance of the problem, where independent individual character controllers would fail to account for the inherent coupling of their respective motions through those physical and behavioral interactions. Various types of motions/behaviors are controlled with only the one single formulation that we propose, and some examples of the original motions the framework allows are presented in the accompanying video.
ABSTRACT
We propose to tackle in this paper the problem of controlling whole-body humanoid robot behavior through non-invasive brain-machine interfacing (BMI), motivated by the perspective of mapping human motor control strategies to human-like mechanical avatar. Our solution is based on the adequate reduction of the controllable dimensionality of a high-DOF humanoid motion in line with the state-of-the-art possibilities of non-invasive BMI technologies, leaving the complement subspace part of the motion to be planned and executed by an autonomous humanoid whole-body motion planning and control framework. The results are shown in full physics-based simulation of a 36-degree-of-freedom humanoid motion controlled by a user through EEG-extracted brain signals generated with motor imagery task.