Most research so far on hierarchical multi-task control with strict priority requires exact
dynamic and kinematic models. However, when a robot picks up tools of unknown lengths …

In recent years, automatic mobile robots (AMRs) have been widely concerned in various
fields, such as material handling, unmanned aerial vehicle (UAV) cruise, automatic factories …

We have extended the task-space multiobjective controllers that write as quadratic programs
(QPs) to handle multirobot systems as a single centralized control. The idea is to assemble …

The control of a robot in its task space is a standard approach nowadays. If the system is
kinematically redundant with respect to this goal, one can even execute additional subtasks …

By incorporating the redefined error monitor function into the network design, an error
redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to …

Hierarchical impedance-based tracking control has attracted much interest recently due to
its advantages of no external forces/torques feedback and inertia reshaping. Desired …

In this paper, we focus on the tracking problem of a dual-arm robot (DAR) with prescribed
performance and unknown input backlash-like hysteresis. Considering this problem …

This article presents a model predictive control (MPC) method for redundant robots
controlling multiple hierarchical tasks formulated as multilayer constrained optimal control …

In trajectory tracking and interaction control of robots, two fundamentally different concepts
define the boundaries within which most nonlinear model-based approaches can be …

Task-space quadratic programming (QP) is an elegant approach for controlling robots
subject to constraints. Yet, in the case of kinematic-controlled (ie, high-gain position or …