Space situational awareness (SSA) plays an important role in maintaining space advantages. Task planning is one of the key technologies SSA to allocate multiple tasks satellites, so that a satellite may be allocated supervise objects, and object supervised by satellites. This paper proposes hierarchical distributed task-planning framework for systems with focus on fast effective task customized...

Task-space quadratic programming (QP) is an elegant approach for controlling robots subject to constraints. Yet, in the case of kinematic-controlled (i.e., high-gain position or velocity) robots, closed-loop QP control scheme can be prone instability depending on how gains related tasks constraints are chosen. In this article, we address such shortcomings. First, highlight nonrobustness system ...

The simple act of standing up is an important and essential motor behavior that most humans and animals achieve with ease. Yet, maintaining standing balance involves complex sensorimotor transformations that must continually integrate a large array of sensory inputs and coordinate multiple motor outputs to muscles throughout the body. Multiple, redundant local sensory signals are integrated to ...

introduction: the current study aimed to elucidate the role of preparatory cognitive control in decision making and its neural correlates using functional magnetic resonance imaging (fmri). to this effect, by employing a series of new cognitive tasks, we assessed the role of preparatory cognitive control in monetary (risky) decision making. methods: the participants had to decide between a risk...

Abstract Whenrobots physically interact with the environment, compliant behaviors should be imposed to prevent damages all entities involved in interaction. Moreover, during physical interactions, appropriate pose controllers are usually based on robot dynamics, which ill-conditioning of joint-space inertia matrix may lead poor performance or even instability. When control is not precise, large...

Multi-objective control systems for complex robots usually have to handle multiple prioritized tasks. Most existing hierarchical control techniques handle either strict task priorities by using null-space projectors or a sequence of quadratic programs; or non strict task priorities by using a weighting strategy. This paper proposes a novel approach to handle both strict and non-strict prioritie...

We study the stability properties of nonlinear multi-task regression in reproducing Hilbert spaces with operator-valued kernels. Such kernels, a.k.a. multi-task kernels, are appropriate for learning problems with nonscalar outputs like multi-task learning and structured output prediction. We show that multi-task kernel regression algorithms are uniformly stable in the general case of infinite-d...