  This paper presents an interconnected control-planning strategy for redundant
manipulators, subject to system and environmental constraints. The method
incorporates low-level control characteristics and high-level planning
components into a robust strategy for manipulators acting in complex
environments, subject to joint limits. This strategy is formulated using an
adaptive control rule, the estimated dynamic model of the robotic system and
the nullspace of the linearized constraints. A path is generated that takes
into account the capabilities of the platform. The proposed method is
computationally efficient, enabling its implementation on a real multi-body
robotic system. Through experimental results with a 7 DOF manipulator, we
demonstrate the performance of the method in real-world scenarios.
