3 citations · 9 across the 22 of their papers we have counts for
21 papers · 1 filter
Continual Humanoid Motion Learning
Zhewen He, Hao Huang, Geeta Chandra Raju Bethala +4
Humanoid whole-body controllers can now track a diverse set of dynamic motions, but they are typically trained offline and then frozen, so teaching such a controller a new skill te…
Local Path Planning and Obstacle Avoidance for an Omnicopter Platform
Mikolaj Helinski, Spilios Theodoulis, Mahmoud Hamandi +3
Autonomous unmanned aerial vehicles (UAVs) increasingly operate in cluttered environments where global planners such as RRT* are not directly deployable at control rates. This pape…
Dual Stress: Runtime Safety Monitoring for Safety-Constrained MPC Navigation
Jamil Chahine, Wenqi Cai, John Abanes +1
Runtime hazard monitors for autonomous naviga- tion are conventionally built from geometric quantities: predicted clearance, time to collision, and required deceleration. A model-p…
Hölder Signed Distance: A Differentiable, Signed, Parallelizable Metric for Robotics
Felipe Bartelt, Ali Umut Kaypak, Anthony Tzes +3
Computing distances between sets is essential in robotic motion planning and control, where differentiable gradients enable real-time optimization. The Euclidean Signed Distance Fu…
Learning Adaptive Safety Margins for Visual Navigation
Junyi Hu, Shuaihang Yuan, Geeta Chandra Raju Bethala +2
Robots in cluttered indoor spaces often fail not because they cannot generate collision-free paths, but because a fixed safety margin is mis-calibrated: conservative margins cause…
Immersive Social Interaction with VR and LLM-Assisted Humanoids
Niraj Pudasaini, Geeta Chandra Raju Bethala, Pranav Doma +2
Humanoid robots can extend human presence to remote, constrained, or hazardous environments, but existing teleoperation interfaces often require physically demanding motion trackin…
Safe Human-to-Humanoid Motion Imitation Using Control Barrier Functions
Wenqi Cai, John Abanes, Nikolaos Evangeliou +1
Ensuring operational safety is critical for human-to-humanoid motion imitation. This paper presents a vision-based framework that enables a humanoid robot to imitate human movement…
Cost-Matching Model Predictive Control for Efficient Reinforcement Learning in Humanoid Locomotion
Wenqi Cai, Kyriakos G. Vamvoudakis, Sébastien Gros +1
In this paper, we propose a cost-matching approach for optimal humanoid locomotion within a Model Predictive Control (MPC)-based Reinforcement Learning (RL) framework. A parameteri…
One-shot Adaptation of Humanoid Whole-body Motion with Walking Priors
Hao Huang, Geeta Chandra Raju Bethala, Shuaihang Yuan +4
Whole-body humanoid motion represents a fundamental challenge in robotics, requiring balance, coordination, and adaptability to enable human-like behaviors. However, existing metho…
SLAM-based Safe Indoor Exploration Strategy
Omar Mostafa, Nikolaos Evangeliou, Anthony Tzes
This paper suggests a 2D exploration strategy for a planar space cluttered with obstacles. Rather than using point robots capable of adjusting their position and altitude instantly…
Wavelet Policy: Lifting Scheme for Policy Learning in Long-Horizon Tasks
Hao Huang, Shuaihang Yuan, Geeta Chandra Raju Bethala +3
Policy learning focuses on devising strategies for agents in embodied artificial intelligence systems to perform optimal actions based on their perceived states. One of the key cha…
A Differentiable Distance Metric for Robotics Through Generalized Alternating Projection
Vinicius M. Gonçalves, Shiqing Wei, Eduardo Malacarne S. de Souza +3
In many robotics applications, it is necessary to compute not only the distance between the robot and the environment, but also its derivative - for example, when using control bar…
FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling
Yijie Deng, Shuaihang Yuan, Congcong Wen +4
Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot navigation. Existing approaches either…
H2-COMPACT: Human-Humanoid Co-Manipulation via Adaptive Contact Trajectory Policies
Geeta Chandra Raju Bethala, Hao Huang, Niraj Pudasaini +5
We present a hierarchical policy-learning framework that enables a legged humanoid to cooperatively carry extended loads with a human partner using only haptic cues for intent infe…
GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance
Shuaihang Yuan, Hao Huang, Yu Hao +3
Zero-Shot Object Goal Navigation (ZS-OGN) enables robots or agents to navigate toward objects of unseen categories without object-specific training. Traditional approaches often le…
Reliable Semantic Understanding for Real World Zero-shot Object Goal Navigation
Halil Utku Unlu, Shuaihang Yuan, Congcong Wen +3
We introduce an innovative approach to advancing semantic understanding in zero-shot object goal navigation (ZS-OGN), enhancing the autonomy of robots in unfamiliar environments. T…
Exploring the Reliability of Foundation Model-Based Frontier Selection in Zero-Shot Object Goal Navigation
Shuaihang Yuan, Halil Utku Unlu, Hao Huang +3
In this paper, we present a novel method for reliable frontier selection in Zero-Shot Object Goal Navigation (ZS-OGN), enhancing robotic navigation systems with foundation models t…
RCM-Constrained Manipulator Trajectory Tracking Using Differential Kinematics Control
Omar Rayyan, Vinicius Gonçalves, Nikolaos Evangeliou +1
This paper proposes an approach for controlling surgical robotic systems, while complying with the Remote Center of Motion (RCM) constraint in Robot-Assisted Minimally Invasive Sur…
Socially-Aware Robot Navigation Enhanced by Bidirectional Natural Language Conversations Using Large Language Models
Congcong Wen, Yifan Liu, Geeta Chandra Raju Bethala +7
Robot navigation is crucial across various domains, yet traditional methods focus on efficiency and obstacle avoidance, often overlooking human behavior in shared spaces. With the…
Robotic Shepherding in Cluttered and Unknown Environments using Control Barrier Functions
Mahmoud Hamandi, Farshad Khorrami, Anthony Tzes
This paper introduces a novel control methodology designed to guide a collective of robotic-sheep in a cluttered and unknown environment using robotic-dogs. The dog-agents continuo…
Efficient and Distributed Large-Scale 3D Map Registration using Tomographic Features
Halil Utku Unlu, Anthony Tzes, Prashanth Krishnamurthy +1
A robust, resource-efficient, distributed, and minimally parameterized 3D map matching and merging algorithm is proposed. The suggested algorithm utilizes tomographic features from…