Tootfinder

Robust Embodied Self-Identification of Morphology in Damaged Multi-Legged Robots
Sahand Farghdani, Mili Patel, Robin Chhabra
https://arxiv.org/abs/2506.19984

Robust Embodied Self-Identification of Morphology in Damaged Multi-Legged Robots
Multi-legged robots (MLRs) are vulnerable to leg damage during complex missions, which can impair their performance. This paper presents a self-modeling and damage identification algorithm that enables autonomous adaptation to partial or complete leg loss using only data from a low-cost IMU. A novel FFT-based filter is introduced to address time-inconsistent signals, improving damage detection by comparing body orientation between the robot and its model. The proposed method identifies damaged …

Evolutionary Gait Reconfiguration in Damaged Legged Robots
Sahand Farghdani, Robin Chhabra
https://arxiv.org/abs/2506.19968 https://a…

Evolutionary Gait Reconfiguration in Damaged Legged Robots
Multi-legged robots deployed in complex missions are susceptible to physical damage in their legs, impairing task performance and potentially compromising mission success. This letter presents a rapid, training-free damage recovery algorithm for legged robots subject to partial or complete loss of functional legs. The proposed method first stabilizes locomotion by generating a new gait sequence and subsequently optimally reconfigures leg gaits via a developed differential evolution algorithm to…

This https://arxiv.org/abs/2410.00059 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

IDEA: An Inverse Domain Expert Adaptation Based Active DNN IP Protection Method
Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as watermarking and fingerprinting attempt to prove the ownership upon IP violation, but they are often too late to stop catastrophic damage of IP abuse and too feeble against strong adversaries. In this paper, we propose IDEA, an Inverse Domain Expert Adaptation based…

Simulation of irradiated hybrid planar pixels modules at fluences expected at HL-LHC
Marco Bomben
https://arxiv.org/abs/2506.10823 https://

Simulation of irradiated hybrid planar pixels modules at fluences expected at HL-LHC
Signal loss is the main limitation on tracking/vertexing performance due to radiation damage effect to hybrid pixel detectors when irradiated at fluences expected at High Luminosity LHC (HL-LHC). It is important to have reliable predictions on the charge collection performance after irradiation in order to predict operational voltage values and test tracking algorithms robustness. In this paper the validation of combined TCAD and Monte Carlo simulations of hybrid silicon planar pixels sensors w…