  Safety and automatic control are extremely important when operating
manipulators. For large engineering manipulators, the main challenge is to
accurately recognize the posture of all arm segments. In classical sensing
methods, the accuracy of an inclinometer is easily affected by the elastic
deformation in the manipulator's arms. This results in big error accumulations
when sensing the angle of joints between arms one by one. In addition, the
sensing method based on machine vision is not suitable for such kind of outdoor
working situation yet. In this paper, we propose a novel posture positioning
method for multi-joint manipulators based on wireless sensor network
localization. The posture sensing problem is formulated as a
Nearest-Euclidean-Distance-Matrix (NEDM) model. The resulting approach is
referred to as EDM-based posture positioning approach (EPP) and it satisfies
the following guiding principles: (i) The posture of each arm segment on a
multi-joint manipulator must be estimated as accurately as possible; (ii) The
approach must be computationally fast; (iii) The designed approach should not
be susceptible to obstructions. To further improve accuracy, we explore the
inherent structure of manipulators, i.e., fixed-arm length. This is naturally
presented as linear constraints in the NEDM model. For concrete pumps, a
typical multi-joint manipulator, the mechanical property that all arm segments
always lie in a 2D plane is used for dimension-reduction operation. Simulation
and experimental results show that the proposed method provides efficient
solutions for posture sensing problem and can obtain preferable localization
performance with faster speed than applying the existing localization methods.
