Multi-light acquisitions and modeling are well-studied techniques for characterizing surface geometry, widely used in the cultural heritage field. Current systems that are used to perform this kind of acquisition are mainly free-form or dome-based. Both of them have constraints in terms of reproducibility, limitations on the size of objects being acquired, speed, and portability. This paper presents a novel robotic arm-based system design, which we call LightBot, as well as its applications in reflectance transformation imaging (RTI) in particular. The proposed model alleviates some of the limitations observed in the case of free-form or dome-based systems. It allows the automation and reproducibility of one or a series of acquisitions adapting to a given surface in two-dimensional space.

Gait generation in its realization stage in majority of bipeds involves inverse dynamics model with the need of pre-determined joint trajectories and the zero moment point method for final postural stability adjustments. This requires generation of such joint trajectories, where the zero moment point criterion is fulfilled and the human-like posture is kept. Such task is complex and still misses the universal solution. Preserving natural (human-like) and stable body posture under acting disturbances is an issue too. High computational costs, problem with disturbances rejection and controller complexity are the major disadvantages associated with such approaches. This article presents a method for motion control with forward dynamics model and ground reaction forces as the reference values. The ground reaction forces measured during real human walking are utilized here. A MATLAB/Simulink framework is used for testing the proposed synthesis of bipedal locomotion. The ground reaction forces recorded during the walk with different footwear are applied as the references. The obtained motion patterns and postures are compared with those of the human. Obtained results were satisfactory and justified the proposed approach.