LTE-Advanced networking standard introduces fixed relays as one of the ways to support the ambitious performance requirements for next-generation network services. The relays are introduced to increase the available capacity or to extend the coverage of the network. Balancing the dynamic interference scenarios and the complex resource management in relay-assisted networks presents one of the key challenges for the further development of LTE-A. This paper introduces the challenge of adaptive resource management and identifies simple adaptive scheduling methods based on channel quality information. The paper then utilizes a comprehensive simulation tool to show clear throughput benefits of using adaptive resource management for either the cell edge users or users experiencing very good signal-to-interference ratio, depending on the system objective.

The most widely used technique for generating whole-body motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost. To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot.

We presented our works relative to anthropomorphic motions. We performed task recognition, full-dynamic motion generation, motion retargeting and editing in a unified framework: the stack of tasks. Thanks to the genericity of the task function formalism, our works can be further extended. For example, for the recognition, the use of the task function formalism applied to human motion is currently investigated. Also, preliminary results on the real robot for the retargeting and editing method have been obtained.

Control methods based on a hierarchy of tasks provide a fast, easily-modifiable, and accurate way of generating a motion. In this paper, we propose to extend this hierarchical approach by using a cascade of quadratic programs to handle simultaneously the robot dynamics, inequality and equality constraints, and multiple non-coplanar unilateral contacts. First, we detail the proposed generic inverse-dynamics solver. Then, we prove that the model used to handle contacts encompasses the classical zero-moment-point balance condition. Finally, as an example of the capabilities of the method, we generate a complex motion where the humanoid robot HRP2 sits down on an armchair, using the armrests as additional contacts, while ensuring joint position and velocity limits.