1 citations · 1 across the 5 of their papers we have counts for
7 papers
SiteEvo: An LLM Agent for Autonomous Discovery of Site-Adaptive Massive MIMO Detectors
Jiajia Guo, Chao-Kai Wen, Shi Jin +1
Designing a massive multiple-input multiple-output (MIMO) detector that is tailored to each specific deployment site can improve detection performance, yet most existing detectors,…
Dimension of affine iterated function systems on
Jialun Li, Wenyu Pan, Zhiyuan Zhang
Let be an affine iterated function system on with attractor , and let be an associated self-affine measure. Assume that the $M_…
Path Planning and Reinforcement Learning-Driven Control of On-Orbit Free-Flying Multi-Arm Robots
Álvaro Belmonte-Baeza, José Luis Ramón, Leonard Felicetti +2
This paper presents a hybrid approach that integrates trajectory optimization (TO) and reinforcement learning (RL) for motion planning and control of free-flying multi-arm robots i…
AIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired
Luis Marquez-Carpintero, Francisco Gomez-Donoso, Zuria Bauer +6
This paper presents AIDEN, an artificial intelligence-based assistant designed to enhance the autonomy and daily quality of life of visually impaired individuals, who often struggl…
Autonomous Legged Mobile Manipulation for Lunar Surface Operations via Constrained Reinforcement Learning
Alvaro Belmonte-Baeza, Miguel Cazorla, Gabriel J. García +2
Robotics plays a pivotal role in planetary science and exploration, where autonomous and reliable systems are crucial due to the risks and challenges inherent to space environments…
Optimal path planning and weighted control of a four-arm robot in on-orbit servicing
Celia Redondo-Verdú, José L. Ramón, Álvaro Belmonte-Baeza +2
This paper presents a trajectory optimization and control approach for the guidance of an orbital four-arm robot in extravehicular activities. The robot operates near the target sp…
CLAD: A Contrastive Learning based Approach for Background Debiasing
Ke Wang, Harshitha Machiraju, Oh-Hyeon Choung +2
Convolutional neural networks (CNNs) have achieved superhuman performance in multiple vision tasks, especially image classification. However, unlike humans, CNNs leverage spurious…