60 accepted papers
Collision detection is a fundamental problem in robotics, but handling collisions between non-convex objects remains challenging. A common approach for representing non-convex geometry is a signed distance function (SDF). Voxel-based SDF (VoxelSDF) enables fast distance queries but suffers from disc…
Robotic manipulation commonly involves pick-and-place tasks in which regrasp may be necessary for low-dexterity manipulators. Many existing approaches rely on sampling, which becomes inefficient when repeated regrasp is required in high-dimensional configuration spaces. We propose a modular planning…
Safe, precise teleoperation demands a third-person 3D view that reveals collision clearances and task-critical geometry in full detail. Yet most systems still rely on live camera streams that offer tunnel-vision perspectives and weak depth cues, hiding hazards and denying operators the spatial conte…
Safe, precise teleoperation demands a third-person 3D view that reveals collision clearances and task-critical geometry in full detail. Yet most systems still rely on live camera streams that offer tunnel-vision perspectives and weak depth cues, hiding hazards and denying operators the spatial conte
Vision-language models (VLMs) have achieved impressive results on single-view vision tasks, but lack the multi-view spatial reasoning capabilities essential for embodied AI systems to understand 3D environments and manipulate objects across different viewpoints. In this work, we introduce Cross-View
Unit testing is a core practice in programming, enabling systematic evaluation of programs produced by human developers or large language models (LLMs). Given the challenges in writing comprehensive unit tests, LLMs have been employed to automate unit test generation, yet methods for training LLMs t…
We present a practical system that supports in-depth analysis of cryptocurrency markets through timeline-based event detection and contextual summarization. Our framework processes continuous news streams, identifies price-relevant events, and organizes them into semantic timelines with concise back
We propose a novel inverse kinematics (IK) solver based on an optimization–simulation duality, in which the conventional optimization-based IK problem is reformulated as a forward dynamics simulation of a virtual mechanical system. The IK solution emerges as the equilibrium of this system, correspon
Tendon-driven Continuum Robots (TDCRs) are widely used in confined operating systems due to their thin shape, flexibility, and compliance making them easily deployable in narrow or contact-rich environments. However, real-time safe control near obstacles remains challenging. Computationally expensiv…
Hand tracking plays a key role in capturing and transferring dexterous human manipulation skills to robots. However, achieving reliable tracking across diverse conditions and during complex interactions (e.g., object manipulation) remains challenging. A promising solution is to combine wearable sens…
A signed distance field (SDF) is a widely used geometric representation for robust collision detection between complex geometries, which is crucial for contact-rich simulations. While numerous works have studied SDF representations and SDF-based collision detection, achieving both memory efficiency …
Utilizing the complex inter-variable causal relationships within multivariate time-series provides a promising avenue toward more robust and reliable multivariate time-series anomaly detection (MTSAD) but remains an underexplored area of research. This paper proposes Causality-Aware contrastive lear…
We propose a novel cross-source point cloud registration (CSPR) method for USV-AAV cooperation in lentic environments. In the wild outdoors, which is the typical working domain of the USV-AAV team, CSPR faces significant challenges due to platform-domain problems (complex unstructured surroundings a
This paper presents a framework designed to tackle a range of planning problems arise in manipulation, which typically involve complex geometric-physical reasoning related to contact and dynamic constraints. We introduce the Contact Factor Graph (CFG) to graphically model these diverse factors, enab
In this paper, we implement the GPU-accelerated subsystem-based Alternating Direction Method of Multipliers (SubADMM) for interactive simulation. The challenging objective for interactive simulations is to deliver realistic results under tight performance, even for large-scale scenarios. We aim to a
Recent advances in large language models (LLMs) have led to a growing interest in developing LLM-based agents for automating web tasks. However, these agents often struggle with even simple tasks on real-world websites due to their limited capability to understand and process complex web page struct…
Recent advancements in large language models (LLMs) have enabled in-context learning (ICL)-based methods that significantly outperform fine-tuning approaches for text-to-SQL tasks. However, their performance is still considerably lower than that of human experts on benchmarks that include complex sc…
Narrow passage path planning is a prevalent problem from industrial to household sites, often facing difficulties in finding feasible paths or requiring excessive computational resources. Given that deep penetration into the environment can cause optimization failure, we propose a framework to ensur
We propose a novel real-time excavation trajectory modulation framework on a slope for an autonomous excavator with a low-level digital kinematic control as common for hydraulic industrial excavators. Excavation on a slope is challenging because of a higher risk of slips and rollovers. To deal with
Recent advances in Reinforcement Learning (RL) have demonstrated promising results in autonomous car racing. However, two fundamental challenges remain: sparse rewards, which hinder efficient learning process, and the quality of demonstrations, which directly affects the effectiveness of RL from Dem
Shape abstraction, simplifying shape representation into a set of primitives, is a fundamental topic in computer vision. The choice of primitives shapes the structure of world understanding, yet achieving both high abstraction accuracy and versatility remains challenging. In this paper, we introduce…
In this paper, we introduce time-correlated model predictive path integral (TC-MPPI), a novel approach to mitigate action noise in sampling-based control methods. Unlike conventional smoothing techniques that rely on post-processing or additional state variables, TC-MPPI directly incorporates tempor
Collision detection is a fundamental problem across various fields such as robotics, physical simulation, and computer graphics. While numerous studies have provided efficient solutions, based on the well-known Gilbert, Johnson, and Keerthi (GJK) algorithm and Expanding Polytope Algorithm (EPA), exi…
In this paper, we propose a real-time clothoid tree-based path planning for self-driving robots. Clothoids, curves that exhibit linear curvature profiles, play an important role in road design and path planning due to their appealing properties. Nevertheless, their real-time applications face consid…
Sequence modeling faces challenges in capturing long-range dependencies across diverse tasks. Recent linear and transformer-based forecasters have shown superior performance in time series forecasting. However, they are constrained by their inherent inability to effectively address long-range depend…
In this paper, we present a novel trajectory planning method for externally-actuated modular manipulators (EAMMs), consisting of multiple rotor-actuated links with joints that can be either locked or unlocked. This joint-locking feature allows effective balancing of the payload capacity and dexterit…
Ultra-wideband (UWB) communication technology has gained attention in robotics due to its ability to provide range measurements possibly with centimeter-level accuracy. Nevertheless, practical UWB range measurements are susceptible to disturbances from multiple sources, including the anisotropic cha…
The gradient of typical differentiable simulation is uninformative for two reasons: 1) non-smoothness in contact dynamics not considered properly, and 2) excessive local minima generated from the smoothing procedure. To tackle this issue, we first propose differentiable contact dynamics with an inva…
In this paper, we present a new multibody physics simulation framework that utilizes the subsystem-based struc-ture and the Alternating Direction Method of Multiplier (ADMM). The major challenge in simulating complex high degree of freedom systems is a large number of coupled con-straints and large-…
Three-dimensional (3D) reconstruction of wiry structures from vision suffers from thin geometry, lack of texture, and severe self-occlusions. We propose an online 3D edge reconstruction framework that uses monocular image sequences to reconstruct the wiry structures whose skeletons are mainly straig
In this paper, a novel planned trajectory classification method (PTCM) is proposed to evaluate the safety of the car- like four-wheeled mobile robots (4-WMRs) with Ackermann steering and high-stiffness suspensions. To classify a planned trajectory to be safe or unsafe before the 4-WMR actually follo
In recent years, prompt tuning has proven effective in adapting pre-trained vision-language models to down- stream tasks. These methods aim to adapt the pre-trained models by introducing learnable prompts while keeping pre- trained weights frozen. However, learnable prompts can affect the internal r…
We propose novel symmetry-based modeling and hybrid orientation-force control frameworks for cutaneous haptic device (CHD) to generate precise three degree-of-freedom (DoF) contact force on the fingertip robustly against user variability. The CHD hardware is designed in a form of an underactuated ca…
We propose a new neck design for legged robots to achieve robust visual-inertial state estimation in dynamic locomotion. While visual-inertial state estimation is widely used in robotics, it has a problem of being disturbed by the impacts and vibration generated when legged robots move dynamically.
For many robotic manipulation and contact tasks, it is crucial to accurately estimate uncertain object poses, for which certain geometry and sensor information are fused in some optimal fashion. Previous results for this problem primarily adopt sampling-based or end-to-end learning methods, which ye…
This paper proposes an external wrench estimation method for modular manipulators, where each link module is driven with external actuation (e.g., rotors, thrusters) and inter-module joints can be locked to increase end-effector stiffness or workforce of the manipulator. For such systems, the common…
The recent advances of deep learning have dramatically changed how machine learning, especially in the domain of natural language processing, can be applied to legal domain. However, this shift to the data-driven approaches calls for larger and more diverse datasets, which are nevertheless still sma…
This work proposes a novel precision motion control framework of robotized industrial hydraulic excavators via data-driven model inversion. Rather than employing a single neural network to approximate the whole excavator dynamics, including input delays and dead-zones, we construct a physics-inspire
We propose a novel distributed control framework for teleoperated platooning of multiple three-dimensional (3D) fixed-wing unmanned aerial vehicles (UAVs), consisting of the following two layers: 1) virtual frame layer, which generates the target 3D nonholonomic motion of the virtual nonholonomic fr
We propose a novel real-time physically-accurate simulator for long flexible cable manipulation. We first discretize the cable into multiple rigid link segments, each with complementarity-based contact model and inter-segment compliant coupling; and partition the cable into a number of subsystems, e…
We introduce Korean Language Understanding Evaluation (KLUE) benchmark. KLUE is a collection of eight Korean natural language understanding (NLU) tasks, including Topic Classification, Semantic Textual Similarity, Natural LanguageInference, Named Entity Recognition, Relation Extraction, Dependency P…
We propose a novel real-time physically-accurate simulation framework for the snap connection process. For this, we first notice the peculiarities of the process, namely, small/smooth deformation, stiff connector and segmented contact. We then design our simulation to fully exploit these peculiariti…
The RVM (Robot-based Vibration Suppression Modules) is proposed for the manipulation and transport of a large flexible object. Since the RVM is easily attachable/detachable to the object, this RVM allows distributing over the manipulated object so that it is scalable to the object size. The composit…
We propose a novel excavation (i.e., digging) trajectory planning framework for industrial autonomous robotic excavators, which emulates the strategies of human expert operators to optimize the excavation of (complex/unmodellable) soils while also upholding robustness and safety in practice. First,…
In this paper, we propose a novel sim-to-real framework to solve bolting tasks with tight tolerance and complex contact geometry which are hard to be modeled. The sim-to-real has desirable features in terms of cost and safety, however, that of the assembly task is rare due to the lack of simulator,…
We propose a novel data-driven learning-based contact clustering (i.e., of contact points and contact normals) framework for rigid-body robot simulation, with its accuracy established/verified by real experimental data. We first construct an experimental robotic setup with force/torque (F/T) sensors…
We propose a novel model-free optimal estimation and sensor placement framework for a high-DOF (degree-of-freedom) EKC (elastic kinematic chain) with only a limited number of IMU (inertial measurement unit) sensors based on POD (proper orthogonal decomposition) and MAP (maximum a posteriori) estimat…
We propose a novel fast simulation framework for soft objects/robots with intermittent contacts, whose contact areas/locations can be varying. We first perform a balanced model reduction of the full-order FEM (finite element method) model for each contact mode with the contact forcing as the input a…
We present a novel pose and posture estimation framework of aerial skeleton system for outdoor flying. To exploit redundant/independent sensing while rendering the system “modular”, we attach an IMU (inertial measurement unit) sensor and a GNSS (global navigation satellite system) module on each lin…
Electrical motor and hydraulic actuation widely-used in robotics are “internal actuation” with their actuators sitting at the joint between two links. This internal actuation is fundamentally limiting to construct a large-size dexterously-articulated robot, since any external force (and its own link…
The MAGMaS (Multiple Aerial-Ground Manipulator System) was proposed in [1] as a heterogeneous system composed of multiple ground (mobile) manipulators and aerial robots to collaboratively manipulate a long/large-sized object and demonstrated therein for rigid load manipulation. Here, we extend this…
We propose a novel real-time algorithm to estimate the full three-dimensional individual tire forces (i.e., vertical, longitudinal as well as lateral) of a car-like rearwheel-driven four wheel wheeled mobile robots equipped with onboard navigation sensors and wheel encoders. The key enabling idea fo…
We propose a novel haptic rendering scheme based on passive midpoint integrator (PMI), which is an extension of our prior non-iterative passive mechanical integrator (NPMI) to maximal coordinates for simulation of complex articulated rigid bodies and to multi-point intermittent contact with the line…
We develop a novel passivity-based control framework of a manipulator-stage system sitting on a vertical flexible beam. We first model the vertical flexible beam by using Euler-Bernoulli theory and modal approximation while utilizing certain boundary conditions to take into account the effect of the…
We propose a novel multi-rotor flying platform, ODAR (omni-directional aerial robot), which is fully-actuated (i.e., can assume arbitrary motion in SE(3) or generate arbitrary control wrench in se(3)) by six opportunistically distributed rotors, each driven by reversible ESC (electronic speed contro…
We propose a new aerial tool operation system consisting of multiple quadrotors connected to a tool by spherical joints to perform tool operation tasks. We model the system and show that the attitude dynamics of each quadrotor is decoupled from the tool dynamics, so that we can consider the quadroto…
We propose an hierarchical control framework for multiple cooperative quadrotor-manipulator systems, which allows us to endow the common grasped object with a user-specified desired behavior (e.g., trajectory tracking, compliant interaction, etc.). To achieve this, our control framework consists of…
We propose a novel whole-body multi-modal semiautonomous teleoperation framework for mobile manipulator systems, which consists of: 1) Motion capture and whole-body motion mapping to allow the operator to intuitively teleoperate the mobile manipulator without being constrained by the master interfac…