We present a highly accurate and efficient, yet simple, two-stage voting scheme for distinguishing inlier 3D correspondences by densely assessing and ranking their local and global geometric consistencies. The strength of the proposed method stems from both the novel idea of post-validated voting set, as well as single-point superimposition transforms, which are computationally cheap and avoid rotational ambiguities. Using a well-known dataset consisting of various 3D models and numerous scenes that include different occlusion rates, the proposed scheme is evaluated against state-of-the-art 3D voting schemes, in terms of both the correspondence PR (precision-recall) AUC (area under curve), and the execution time. A total of 374 experiments were conducted for each method, which involved a combination of four models, 50 scenes, and two down-samplings. The proposed scheme outperforms the state-of-the-art 3D voting schemes in terms of both accuracy and speed. Quantitatively, the proposed scheme scores 97.0% ±12.9% on the PR AUC metric, averaged over all of the experiments, while the two state-of-the-art schemes score 74.2% ±22.2% and 78.3% ±26.4%. Furthermore, the proposed scheme requires only 24.1% ±6.0% of the time consumed by the fastest state-of-the-art scheme. The proposed voting scheme also demonstrates high robustness against occlusions and scarce inliers.

In this paper, we propose objective functions to estimate the principal contact between a unknown manipulated target object and its unknown surroundings from the motion of the object. We derived the objective functions based on the fact that contact involves a pair of geometrical primitives (a point of vertex, a line of edge, and a plane of face) for the singular condition of the calculation for their intersection or their spanned space from the point of view of geometrical algebra. The minimization of the proposed objective functions, which are differential quadratic forms of the Kronecker product of geometrical parameters, efficiently provided us the contact geometries that constrained the object movements. Additionally, the proposed objective functions are fundamentals for identifying contact during compliant manipulation, and we showed that the objective functions provide a clue for contact identification via experiments.

In this paper, we propose an optimization method to determine the design parameters comprising joint displacement parameters in a serial manipulator having small degrees of freedom realizing an approximated target trajectory. Using generalized differential kinematics, we can achieve efficient optimization without solving the inner-loop optimization required to obtain the reachable points.

Recently, the tendon-driven mechanism with variable joint stiffness has received attention for use in the development of a humanoid robot operated in an uncertain environment with physical contact. In this paper, we propose a mechanism to control the position and joint stiffness of a tendon-driven manipulator independently, using dedicated actuators. This mechanism consists of two parts: a component that transforms the movements of the tendons to activate the actuators, and a component that applies tensile forces to adjust the joint stiffness. We named this mechanism “tendon routing resolving inverse kinematics” (TRIK). The methodology for designing this mechanism for various tendon-driven manipulators is presented with several examples. We designed TRIK for a manipulator with one degree of freedom and nonconstant-moment arms. Finally, experiments of variable joint stiffness with nonlinearly elastic components were conducted to validate the proposed mechanism.