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Redundant systems are of interest in engineering because they bring additional capability for a task completion, allowing the system to perform sub-tasks or to improve performances. However, this also means that an extra degree of complexity is added to its resolution. For this purpose, proposed resolution schemes are classically based on the 2-norm minimization, also called pseudo-inverse, whose...
When robots and humans interact in a task, stiffness is necessary for performance, while passive compliance is fundamental for safety. These two factors are the motivation for intrinsic compliant modulation in robots interacting with humans. Variable Stiffness Actuators (VSAs) allow for simultaneous position and stiffness control of a joint, and therefore have been implemented in the realization of...
By far the most popular method of resolving redundant systems involves application of the 2-norm-optimizing Moore-Penrose pseudo-inverse. Pseudo-inverse resolution resolves systems uniquely, continuously, and most notably with simple implementation for general systems. However, resolution using 2-norm fails to exploit general systems' full realizable output space when input bounds are present. The...
In the resolution of redundancy in systems, by far the most popular approach involves optimization with respect to the 2-norm, due to it's ease of use, uniqueness, and continuity of resolution. Due to the 2-norm's inability to consider input bounds, however, such methods fail to exploit systems' full feasible output range. The Cascaded Generalized Inverse (CGI) was introduced to extend the realizable...
In the resolution of redundant systems, two popular resolution schemes, optimization using 2-norm and infinity-norm, have been commonly employed. However, each finds its greatest utility in resolution in very different circumstances. The 2-norm optimizes in analog to minimizing system energy (sometimes by putting large strain on individual actuators). Likewise, the infinity-norm minimizes individual...
Redundancy in systems is valued for its ability to add additional dexterity in task completion, but its utilization implies an added degree of complexity which must be resolved at runtime. The majority of resolution methods have focused on resolution using some variant of the 2-norm optimizing pseudo-inverse. While tractable, the pseudo-inverse fails to consider input bounds and often resolves systems...
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