Environment Exploration
Environment exploration in robotics and AI focuses on enabling agents to efficiently and effectively learn about and navigate unknown environments, optimizing for factors like map creation, sensor fusion, and efficient decision-making. Current research emphasizes leveraging deep learning models, such as neural networks and transformers, for tasks like map prediction, sensor calibration (e.g., LiDAR-camera), and skill acquisition, often incorporating techniques like reinforcement learning and information gain calculations to guide exploration strategies. These advancements have implications for various fields, including autonomous navigation, game design, and personalized healthcare, by improving the robustness and adaptability of AI agents in complex and dynamic settings.
Papers
Exploration Without Maps via Zero-Shot Out-of-Distribution Deep Reinforcement Learning
Shathushan Sivashangaran, Apoorva Khairnar, Azim Eskandarian
Entanglement Definitions for Tethered Robots: Exploration and Analysis
Gianpietro Battocletti, Dimitris Boskos, Domagoj Tolić, Ivana Palunko, Bart De Schutter
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
Luyang Lin, Lingzhi Wang, Xiaoyan Zhao, Jing Li, Kam-Fai Wong
Frame-Wise Breath Detection with Self-Training: An Exploration of Enhancing Breath Naturalness in Text-to-Speech
Dong Yang, Tomoki Koriyama, Yuki Saito
Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model
Zhiwei He, Xing Wang, Wenxiang Jiao, Zhuosheng Zhang, Rui Wang, Shuming Shi, Zhaopeng Tu
Exploration and Improvement of Nerf-based 3D Scene Editing Techniques
Shun Fang, Ming Cui, Xing Feng, Yanan Zhang
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments
Suchetan Saravanan, Corentin Chauffaut, Caroline Chanel, Damien Vivet
Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators
Mahdi Taheri, Natalia Cherezova, Mohammad Saeed Ansari, Maksim Jenihhin, Ali Mahani, Masoud Daneshtalab, Jaan Raik