Dynamic Modeling and Simulation of a Rotating Single Link Flexible Robotic Manipulator Subject to Quick Stops

Single link robotic manipulators are extensively used in industry and research operations. The main design requirement of such manipulators is to minimize link dynamic deflection and its active end vibrations, and obtain high position accuracy during its high speed motion. To achieve these requirements, accurate mathematical modeling and simulation of the initial design, to increase system stability and precision and to obtain very small amplitudes of vibration, should be considered. In this paper the modeling of such robotic arm with a rigid guide and a flexible extensible link subject to quick stops after each complete revolution is considered and its dynamical behavior analyzed. The extensible link which rotates with constant angular velocity has one end constrained to a predefined trajectory. The constrained trajectory allows trajectory control and obstacle avoidance for the active end of the robotic arm. The dynamic evolution of the system is investigated and the flexural response of the flexible link analyzed under the combined effect of clearance and flexibility.

Representation Learning by Learning to Count

We introduce a novel method for representation learning that uses an artificial supervision signal based on counting visual primitives. This supervision signal is obtained from an equivariance relation, which does not require any manual annotation. We relate transformations of images to transformations of the representations. More specifically, we look for the representation that satisfies such relation rather than the transformations that match a given representation. In this paper, we use two image transformations in the context of counting: scaling and tiling. The first transformation exploits the fact that the number of visual primitives should be invariant to scale. The second transformation allows us to equate the total number of visual primitives in each tile to that in the whole image. These two transformations are combined in one constraint and used to train a neural network with a contrastive loss. The proposed task produces representations that perform on par or exceed the state of the art in transfer learning benchmarks.Comment: ICCV 2017(oral

How should we assess the mechanical properties of lower-limb prosthesis technology used in elite sport?: An initial investigation

Despite recent controversy, it is not yet formally recognised how lower-limb prosthesis should be assessed for their performance. To assist in this process, experiments are undertaken to investigate the linearity, stiffness and assessment of feet based energy return prosthesis technology typically used for elite level high speed running. Through initial investigations, it is concluded that static load testing would not be recommended to specify or regulate energy return prostheses for athletes with a lower-limb amputation. Furthermore, an assessment of energy return technology when loaded under dynamic conditions demonstrates changes in mechanical stiffness due to bending and effective blade length variation during motion. Such radical changes of boundary conditions due to loading suggest that any assessment of lower-limb prosthesis technology in the future should use methods that do not assume linear mechanical stiffness. The research into such effects warrants further investigation in the future