37 accepted papers
Language-guided robotic grasping in cluttered environments presents significant challenges due to severe occlusions and complex scene structures, which often hinder accurate target localization. Existing approaches typically suffer from limited observational capabilities, resulting in suboptimal exp…
Although CLIP-like Visual Language Models provide a functional joint feature space for image and text, due to the limitation of the CILP-like model's image input size (e.g., 224), subtle details are lost in the feature representation if we input high-resolution images (e.g., 2240). Our proposed fram…
Accurate visual–inertial simultaneous localization and mapping (VI SLAM) for underwater robots remains a significant challenge due to frequent visual degeneracy and insufficient inertial measurement unit (IMU) motion excitation. In this paper, we present GeVI-SLAM, a gravity-enhanced stereo VI SLAM …
Trajectory planning in unstructured environments is a fundamental and challenging capability for mobile robots. Traditional modular pipelines suffer from latency and cascading errors across perception, localization, mapping, and planning modules. Recent end-to-end learning methods map raw visual obs…
In safety-critical robotics applications, guaranteed and practical uncertainty quantification (UQ) in perception is vital. Many existing works either offer no formal containment guarantee, rely on restrictive modeling assumptions, or focus only on pose estimation rather than a complete SLAM pipeline…
In environments where robots operate with limited global navigation satellite system accessibility, ultra-wideband (UWB) localization technology is a popular auxiliary solution to assist visual–inertial odometry systems. However, current UWB approaches lack 3-D pairwise localization capability and s…
In multi-agent systems, the hybrid active-silent relative localization framework is widely employed, where only active nodes transmit signals. The selection of active nodes, known as node activation, significantly impacts the positioning accuracy. This paper investigates the node activation in ancho…
Language-guided robotic grasping in cluttered environments presents significant challenges due to severe occlusions and complex scene structures, which often hinder accurate target localization. Existing approaches typically suffer from limited observational capabilities, resulting in suboptimal exp
In this letter, we first present a bias-eliminated weighted (Bias-Eli-W) perspective-n-point (PnP) estimator for stereo visual odometry (VO) with provable consistency. Specifically, we develop a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"
Learning 3D parametric shape models of objects has gained popularity in vision and graphics and has showed broad utility in 3D reconstruction, generation, understanding, and simulation. While powerful models exist for humans and animals, equally expressive approaches for modeling plants are lacking.…
Time series modeling presents unique challenges due to autocorrelation in both historical data and future sequences. While current research predominantly addresses autocorrelation within historical data, the correlations among future labels are often overlooked. Specifically, modern forecasting mode…
Although existing 3D perception algorithms have demonstrated significant improvements in performance, their deployment on edge devices continues to encounter critical challenges due to substantial runtime latency. We propose a new benchmark tailored for online evaluation by considering runtime laten
Ultra-wideband (UWB) is a popular technology for robotic localization in global positioning system (GPS)-challenged and vision-obstructed scenarios. In UWB localization systems, distance information is extracted from ToA and ToD timestamp measurements. However, these measurements are easily influenc…
Cryo-electron microscopy (Cryo-EM) is a revolutionizing technique that facilitates the determination of macromolecule structures. To attain high-resolution structures, numerous noisy images should be iteratively aligned and reconstructed into 3D models. The alignment step is the bottleneck of comput…
Ultra-wide band (UWB) systems are gaining popularity for multi-robot localization benefiting from their high-accuracy ranging capabilities. However, current UWB systems fall short in determining orientations and realizing pair-wise localization for neglecting bearing information. Given the importanc…
Can computers perceive the physical properties of objects solely through vision? Research in cognitive science and vision science has shown that humans excel at identifying materials and estimating their physical properties based purely on visual appearance. In this paper we present a novel approach…
Communication in multi-agent reinforcement learning (MARL) has been proven to effectively promote cooperation among agents recently. Since communication in real-world scenarios is vulnerable to noises and adversarial attacks, it is crucial to develop robust communicative MARL technique. However, exi…
This paper applies the exponential decay property of scalable RL theory to a specific scenario where the network structure is a tree, and use KL (Kullback-Leibler) divergence to analyze the propagation of approximation error along the structure over time, in order to quantify its backtracking result…
State estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solutio…
We present Sim-on-Wheels, a safe, realistic, and vehicle-in-loop framework to test autonomous vehicles' performance in the real world under safety-critical scenarios. Sim-on-wheels runs on a self-driving vehicle operating in the physical world. It creates virtual traffic participants with risky beha
Robots often need to accomplish complex tasks in unknown environments, which is a challenging problem, involving autonomous exploration for acquiring necessary scene knowledge and task planning. In traditional approaches, the agent first explores the environment to instantiate a complete planning do
Autonomous exploration and mapping of unknown terrains employing single or multiple robots is an essential task in mobile robotics and has therefore been widely investigated. Nevertheless, given the lack of unified data sets, metrics, and platforms to evaluate the exploration approaches, we develop…
Collaborative perception in unknown environments is a critical task for multi-robot systems. Without external positioning, multi-robot mapping systems have relied on the transfer of place recognition (PR) descriptors or sensor data for the relative pose estimation (RelPose) and share their local map
Disaster areas involving floods and earthquakes are commonly large, with the rescue time being quite tight, suggesting multi-Unmanned Aerial Vehicles (UAV) exploration rather than employing a single UAV. For such scenarios, current UAV exploration is modeled as a Coverage Path Planning (CPP) problem…
Observability is an essential aspect for the performance of a visual Simultaneous Localization and Mapping (SLAM) network. This paper presents a statistical perspective to evaluate the observability of visual SLAM networks and its dependence on network structure. In particular, we first give the gen…
Multi-agent formation as well as obstacle avoid-ance is one of the most actively studied topics in the field of multi-agent systems. Although some classic controllers like model predictive control (MPC) and fuzzy control achieve a certain measure of success, most of them require precise global infor…
We present simultaneous generation and mapping (SGAM), a novel 3D scene generation algorithm. Our goal is to produce a realistic, globally consistent 3D world on a large scale. Achieving this goal is challenging and goes beyond the capacities of existing 3D generation or video generation approaches,…
Deep generative models (DGMs) and their conditional counterparts provide a powerful ability for general-purpose generative modeling of data distributions. However, it remains challenging for existing methods to address advanced conditional generative problems without annotations, which can enable mu…
Text to speech (TTS) is widely used to synthesize personal voice for a target speaker, where a well-trained source TTS model is fine-tuned with few paired adaptation data (speech and its transcripts) on this target speaker. However, in many scenarios, only untranscribed speech data is available for…
Measuring similarity between two images often requires performing complex reasoning along different axes (e.g., color, texture, or shape). Insights into what might be important for measuring similarity can can be provided by annotated attributes, but prior work tends to view these annotations as com…
Typical methods for localisation in multipath environments focus on separating line-of-sight (LoS) from non-line-of-sight (NLoS) paths and only using LoS paths for localisation. A few works exploit NLoS paths but the methods are designed for some special settings. This paper presents a localisation…
The performance of visual 3D reconstruction is affected by camera position dithering, imaging noise and other environmental factors. In this paper, we adopt statistical analysis for camera dithering in visual 3D reconstruction and demonstrate the improvement of reconstruction accuracy brought by cam…
Visual 3D reconstruction is an essential technique in computer vision which restores the 3D model of the scene from multi-view images. In this paper, we propose a statistical framework for the active visual 3D reconstruction. We first derive a closed-form expression to characterize the dependence of…
We present a novel self quality evaluation metric SQE for parameters optimization in the challenging yet critical multi-object tracking task. Current evaluation metrics all require annotated ground truth, thus will fail in the test environment and realistic circumstances prohibiting further optimiza…
Cooperative detection is the foundation for high-level missions in mobile multi-agent networks. Although extensive research has focused on the design of detection schemes for fixed networks, the position uncertainty induced by the mobility of agents has not been fully investigated. In this paper, we…
Direct localization systems with large-scale antenna-arrays can greatly improve the localization accuracy by jointly processing all the observed signals. However, it incurs high communication overhead due to high-dimensional array signal transmission. In this paper, we propose a robust beamspace des…
Wireless networks are growing in the value of application in many areas, in which accurate clock synchronization is required when tasks are performed in a collaborative fashion among nodes. Especially, cooperative synchronization techniques lead to significant performance improvement compared with t…