arxiv_cv
Abstract: Abstract: Multi-View Photometric Stereo (MVPS) is a popular method for fine-detailed 3D
acquisition of an object from images. Despite its outstanding results on
diverse material objects, a typical MVPS experimental setup requires a
well-calibrated li...
#3D Reconstruction#Robotics Perception#Photometric Stereo#Sensor Fusion#Machine Learning for Robotics
arxiv_cv
Abstract: Abstract: Predicting future motion trajectories is a critical capability across domains
such as robotics, autonomous systems, and human activity forecasting, enabling
safer and more intelligent decision-making. This paper proposes a novel,
efficient,...
#Robotics#Predictive Modeling#Multimodal AI#Computer Vision#Human-Robot Interaction
arxiv_cv
Abstract: Abstract: The input-parameter-state estimation capabilities of a novel unscented Kalman
filter is examined herein on both linear and nonlinear systems. The unknown
input is estimated in two stages within each time step. Firstly, the predicted
dynamic...
#State Estimation#System Identification#Control Theory#Kalman Filtering#Real-time Systems
arxiv_cv
Abstract: Abstract: We introduce SigmaCollab, a dataset enabling research on physically situated
human-AI collaboration. The dataset consists of a set of 85 sessions in which
untrained participants were guided by a mixed-reality assistive AI agent in
performin...
#Human-AI Interaction#Human-Robot Collaboration#Mixed Reality#Embodied AI#Dataset Creation
arxiv_cv
Abstract: Abstract: Video Understanding, Scene Interpretation and Commonsense Reasoning are
highly challenging tasks enabling the interpretation of visual information,
allowing agents to perceive, interact with and make rational decisions in its
environment. L...
#Robotics#Artificial Intelligence#Computer Vision#Natural Language Processing#Edge Computing
arxiv_cv
Abstract: Abstract: We introduce iFlyBot-VLA, a large-scale Vision-Language-Action (VLA) model
trained under a novel framework. The main contributions are listed as follows:
(1) a latent action model thoroughly trained on large-scale human and robotic
manipula...
#Robotics#Embodied AI#Vision-Language Models#Robotic Control#Human-Robot Collaboration
arxiv_cv
Abstract: Abstract: Recent advancements in Deep Learning enable hardware-based cognitive systems,
that is, mechatronic systems in general and robotics in particular with
integrated Artificial Intelligence, to interact with dynamic and unstructured
environments...
#Robotics#Edge AI#Cognitive Systems#Mechatronics#Natural Language Generation#Data Privacy#Human-Robot Interaction
arxiv_cv
Abstract: Abstract: Autonomous agents are increasingly expected to operate in complex, dynamic,
and uncertain environments, performing tasks such as manipulation, navigation,
and decision-making. Achieving these capabilities requires agents to understand
the u...
#Robotics#Artificial Intelligence#Autonomous Systems#Machine Learning#Cognitive Robotics#Perception and Action
arxiv_cv
Abstract: Abstract: Tracking strength-demanding activities with wearable sensors like IMUs is
crucial for monitoring muscular strength, endurance, and power. However, there
is a lack of comprehensive datasets capturing these activities. To fill this
gap, we in...
#Human Activity Recognition#Wearable Computing#Biomedical Engineering#Robotics (Human-Robot Interaction)#Machine Learning#Dataset Development
arxiv_ml
Abstract: Abstract: Bike-sharing is an environmentally friendly shared mobility mode, but its
self-loop phenomenon, where bikes are returned to the same station after
several time usage, significantly impacts equity in accessing its services.
Therefore, this s...
#Urban Mobility#Transportation Systems#Spatial Analysis#Machine Learning for Urban Planning#Shared Mobility
arxiv_ml
Abstract: Abstract: In our prior work, we investigated the minimum fuel consumption of a hybrid
electric vehicle (HEV) under a state-of-charge (SOC) balance constraint,
assuming perfect SOC measurements and accurate reference speed profiles. The
constrained op...
#Hybrid Electric Vehicles#Energy Management#Reinforcement Learning#Control Systems#Robustness in Control
arxiv_ml
Abstract: Abstract: Bimanual robotic manipulation is an emerging and critical topic in the
robotics community. Previous works primarily rely on integrated control models
that take the perceptions and states of both arms as inputs to directly predict
their acti...
#Robotics#Control Systems#Machine Learning for Robotics#Human-Robot Interaction (indirectly)#Automation
arxiv_ml
Abstract: Abstract: We argue that sixth-generation (6G) intelligence is not fluent token
prediction but the capacity to imagine and choose -- to simulate future
scenarios, weigh trade-offs, and act with calibrated uncertainty. We reframe
open radio access netw...
#Future Network Intelligence (6G)#AI for Network Control#Reinforcement Learning#Generative AI#Robotics Control#World Models
arxiv_ml
Abstract: Abstract: Large-scale data has driven breakthroughs in robotics, from language models
to vision-language-action models in bimanual manipulation. However, humanoid
robotics lacks equally effective data collection frameworks. Existing humanoid
teleoper...
#Robotics#Humanoid Robots#Data Collection#Reinforcement Learning#Human-Robot Interaction
arxiv_ml
Abstract: Abstract: We introduce a lightweight, real-time motion recognition system that enables
synergic human-machine performance through wearable IMU sensor data, MiniRocket
time-series classification, and responsive multimedia control. By mapping
dancer-sp...
#Human-Machine Interaction#Motion Recognition#Wearable Computing#Creative AI#Performance Art
arxiv_ai
Abstract: Abstract: Synaptic delay has attracted significant attention in neural network dynamics
for integrating and processing complex spatiotemporal information. This paper
introduces a high-throughput Spiking Neural Network (SNN) processor that
supports sy...
#Neuromorphic Computing#Hardware Accelerators for AI#Edge AI#Efficient Neural Networks
arxiv_ai
Abstract: Abstract: Achieving human-like dexterous manipulation remains a major challenge for
general-purpose robots. While Vision-Language-Action (VLA) models show
potential in learning skills from demonstrations, their scalability is limited
by scarce high-q...
#Human-Robot Collaboration for Data Collection#Learning Dexterous Manipulation Skills#Improving Scalability of Robot Learning#Vision-Language Models for Robotics
arxiv_ai
Abstract: Abstract: The Zero-shot Vision-and-Language Navigation in Continuous Environments
(VLN-CE) task requires agents to navigate previously unseen 3D environments
using natural language instructions, without any scene-specific training. A
critical challen...
#Robotics Navigation#Embodied AI#Natural Language Understanding#Reinforcement Learning#Zero-shot Learning
arxiv_ai
Abstract: Abstract: Humanoid agents often struggle to handle flexible and diverse interactions in
open environments. A common solution is to collect massive datasets to train a
highly capable model, but this approach can be prohibitively expensive. In this
pap...
#Embodied AI#Humanoid Robotics#Vision-Language Models#Robot Control#Zero-Shot Learning
arxiv_ai
Abstract: Abstract: Robotic systems have become integral to smart environments, enabling
applications ranging from urban surveillance and automated agriculture to
industrial automation. However, their effective operation in dynamic settings -
such as smart cit...
#Dynamic Reconfiguration of Robotic Systems#Digital Twin Technology for Robotics#Autonomous Adaptation in Smart Environments#Improving Robot Robustness in Dynamic Settings
arxiv_ai
Abstract: Abstract: Today's best-explored routes towards generalist robots center on collecting
ever larger "observations-in actions-out" robotics datasets to train large
end-to-end models, copying a recipe that has worked for vision-language models
(VLMs). We...
#Generalist Robots#Embodied AI#Vision-Language Models#Robotics Control#Zero-Shot Learning
arxiv_ai
Abstract: Abstract: Data scarcity remains a fundamental bottleneck for embodied intelligence.
Existing approaches use large language models (LLMs) to automate gripper-based
simulation generation, but they transfer poorly to dexterous manipulation,
which demand...
#Embodied AI#Robotics Simulation#Data Augmentation#Dexterous Manipulation#Generative Models
arxiv_ai
Abstract: Abstract: Object-Centric Motion Generation (OCMG) is instrumental in advancing
automated manufacturing processes, particularly in domains requiring
high-precision expert robotic motions, such as spray painting and welding. To
realize effective automa...
#Robotic Motion Generation#Deep Learning for Robotics#Automated Manufacturing#Trajectory Optimization
arxiv_ai
Abstract: Abstract: Constructing accurate digital twins of articulated objects is essential for
robotic simulation training and embodied AI world model building, yet
historically requires painstaking manual modeling or multi-stage pipelines. In
this work, we p...
#3D Reconstruction#Robotics Simulation#Embodied AI#Multimodal AI#Generative Models
arxiv_ai
Abstract: Abstract: Most planners ground numeric planning tasks, given in a first-order-like
language, into a ground task representation. However, this can lead to an
exponential blowup in task representation size, which occurs in practice for
hard-to-ground t...
#Automated Planning#AI Planning under Uncertainty#Symbolic AI#State Representation in Planning
arxiv_ai
Abstract: Abstract: In this work, we introduce MO-SeGMan, a Multi-Objective Sequential and Guided
Manipulation planner for highly constrained rearrangement problems. MO-SeGMan
generates object placement sequences that minimize both replanning per object
and ro...
#Robotic Manipulation#Motion Planning#Optimization#Robotics
arxiv_cv
Abstract: Abstract: Vision-language-action (VLA) models aim to understand natural language
instructions and visual observations and to execute corresponding actions as an
embodied agent. Recent work integrates future images into the
understanding-acting loop, ...
#Embodied AI#Robotics#Multimodal Learning#Generative Models#Reinforcement Learning#Vision-Language Models
arxiv_cv
Abstract: Abstract: Reconstructing cardiac electrical activity from body surface electric
potential measurements results in the severely ill-posed inverse problem in
electrocardiography. Many different regularization approaches have been
proposed to improve nu...
#Inverse Problems#Medical Imaging#Electrophysiology#Numerical Methods#Signal Processing
arxiv_cv
Abstract: Abstract: Collaborative perception significantly enhances individual vehicle perception
performance through the exchange of sensory information among agents. However,
real-world deployment faces challenges due to bandwidth constraints and
inevitable ...
#Multi-Agent Systems#Cooperative Perception#Robotics#Sensor Fusion#Autonomous Driving
arxiv_cv
Abstract: Abstract: Spatial reasoning in 3D space is central to human cognition and indispensable
for embodied tasks such as navigation and manipulation. However,
state-of-the-art vision-language models (VLMs) struggle frequently with tasks
as simple as antici...
#Embodied AI#Spatial Reasoning#Vision-Language Models#Robotics#AI for 3D Environments