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Found 9 papers, 1 papers with code
MIRACLE: Inverse Reinforcement and Curriculum Learning Model for Human-inspired Mobile Robot Navigation
In emergency scenarios, mobile robots must navigate like humans, interpreting stimuli to locate potential victims rapidly without interfering with first responders.
MTAC: Hierarchical Reinforcement Learning-based Multi-gait Terrain-adaptive Quadruped Controller
Urban search and rescue missions require rapid first response to minimize loss of life and damage.
DREAM: Decentralized Reinforcement Learning for Exploration and Efficient Energy Management in Multi-Robot Systems
This paper introduces DREAM - Decentralized Reinforcement Learning for Exploration and Efficient Energy Management in Multi-Robot Systems, a comprehensive framework that optimizes the allocation of resources for efficient exploration.
Visibility-Inspired Models of Touch Sensors for Navigation
This paper introduces mathematical models of \sensors\ for mobile robots based on visibility.
Autoencoding Slow Representations for Semi-supervised Data Efficient Regression
We find that slow representations lead to equal or better downstream task performance and data efficiency in different experiment domains when compared to representations without slowness regularization.
DeFINE: Delayed Feedback based Immersive Navigation Environment for Studying Goal-Directed Human Navigation
With the advent of consumer-grade products for presenting an immersive virtual environment (VE), there is a growing interest in utilizing VEs for testing human navigation behavior.
MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations
Extracting and binding salient information from different sensory modalities to determine common features in the environment is a significant challenge in robotics.
ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
RatSLAM is a rat hippocampus-inspired visual Simultaneous Localization and Mapping (SLAM) framework capable of generating semi-metric topological representations of indoor and outdoor environments.
Robotics
Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I
The objective of this handout and in turn the website was to allow the users to develop stand-alone GPs in Python by relying on minimal external dependencies.
