24 accepted papers
Small multirotors demonstrate significant potential due to their simple airframe and human-friendly operation. However, the reduced size results in substantially higher energy consumption, which severely limits their flight endurance and restricts their range of applications. Ornithopters, while off…
This letter presents a comprehensive comparative study of Incremental Nonlinear Dynamic Inversion (INDI) and standard Nonlinear Dynamic Inversion (NDI) for smooth trajectory tracking on Samara Seed-Inspired Single-Actuator Monocopters (SAM). While prior work on SAMs has largely focused on hover stab…
Small multirotors demonstrate significant potential due to their simple airframe and human-friendly operation. However, the reduced size results in substantially higher energy consumption, which severely limits their flight endurance and restricts their range of applications. Ornithopters, while off
Despite their proficiency in general tasks, Multi-modal Large Language Models (MLLMs) struggle with automatic Geometry Problem Solving (GPS), which demands understanding diagrams, interpreting symbols, and performing complex reasoning. This limitation arises from their pre-training on natural images…
Options markets represent one of the most sophisticated segments of the financial ecosystem, with prices that directly reflect market uncertainty. In this paper, we introduce the first reinforcement learning (RL) framework specifically designed for volatility trading through options, focusing on pro…
This letter presents a comprehensive comparative study of Incremental Nonlinear Dynamic Inversion (INDI) and standard Nonlinear Dynamic Inversion (NDI) for smooth trajectory tracking on Samara Seed-Inspired Single-Actuator Monocopters (SAM). While prior work on SAMs has largely focused on hover stab
Accurate and reliable sensor calibration is critical for fusing LiDAR and inertial measurements in autonomous driving. This paper proposes a novel three-stage extrinsic calibration method between LiDAR and GNSS/INS for autonomous driving. The first stage can quickly calibrate the extrinsic parameter…
Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements. However, prevailing methods struggle with intricate scenarios and causal relationships, hindering adaptability and interpretability in varied environments. To address the above p…
Recent advancements in autonomous driving have relied on data-driven approaches, which are widely adopted but face challenges including dataset bias, overfitting, and uninterpretability. Drawing inspiration from the knowledge-driven nature of human driving, we explore the question of how to instill…
Domain shifts such as sensor type changes and geographical situation variations are prevalent in Autonomous Driving (AD), which poses a challenge since AD model relying on the previous domain knowledge can be hardly directly deployed to a new domain without additional costs. In this paper, we provid…
Data augmentation methods to enhance perception performance in adverse weather have recently attracted considerable attention. Most of the LiDAR data augmentation methods post-process the existing dataset by physics-based models or machine-learning methods. However, due to the limited environmental…
Combining motion prediction in LiDAR-based 3D object detection is an effective method for improving overall accuracy, especially the downstream autonomous driving tasks. The recent development of low-cost LiDARs (e.g. Livox LiDAR) enables us to explore such 4D perception systems with a lower budget…
Extrinsic calibration for LiDAR and camera is an essential prerequisite for sensor fusion. Recently, automatic and target-less extrinsic calibration has become the mainstream of academic research. However, geometric feature-based methods still have requirements on the scene. Deep learning methods, w…
Inspired by maple seeds, the self-rotary winged aerial robots reflect the advantages of both multi-rotor aircraft and fixed-wing robots. However, their self-rotating speed is related to the takeoff weight, which may affect their application and flight stabilization. To provide a practical and feasib
Recently, Vehicle-to-Everything (V2X) cooperative perception has attracted increasing attention. Infrastructure sensors play a critical role in this research field; however, how to find the optimal placement of infrastructure sensors is rarely studied. In this paper, we investigate the problem of in…
Visual information can serve as an effective cue for target speaker extraction (TSE) and is vital to improving extraction performance. In this paper, we propose AV-SepFormer, a SepFormer-based attention dual-scale model that utilizes cross- and self-attention to fuse and model features from audio an…
Feature-based methods are a popular method for camera state estimation using event cameras. Due to the spatiotemporal nature of events, all event images exhibit smearing of events analogous to motion blur for a camera under motion. As such, events must be motion compensated to derive a sharp event i…
Sensor-based environmental perception is a crucial step for autonomous driving systems, for which an accurate calibration between multiple sensors plays a critical role. For the calibration of LiDAR and camera, the existing method is generally to calibrate the intrinsic of the camera first and then…
Offline Reinforcement Learning (RL) has demonstrated promising results in various applications by learning policies from previously collected datasets, reducing the need for online exploration and interactions. However, real-world scenarios usually involve partial observability, which brings crucial…
Multi-agent cooperative perception is an increasingly popular topic in the field of autonomous driving, where roadside LiDARs play an essential role. However, how to optimize the placement of roadside LiDARs is a crucial but often overlooked problem. This paper proposes an approach to optimize the p…
Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent system would configure multiple LiDARs (3D Light Detection and Ranging) to cover the distant and near space of the car. The…
In this paper, we introduce a Modular Single Actuator Monocopter (M-SAM), which is capable of flying in both singular configuration and cooperative configuration. From singular mode, M-SAMs can be manually assembled into cooperative mode, using magnetic connectors built into the body of each M-SAM u…
Monocopters are nature-inspired, single-wing, rotating aerial vehicles that fly by spinning their entire body. Meanwhile, bicopters are twin propeller-based aerial vehicles that control their attitude by changing the direction of thrust from the motors using two servos. In this paper, we present a n
This paper addresses the problem of cooperative transport of a point mass hoisted by two aerial robots. Treating the robots as a leader and a follower, the follower stabilizes the system with respect to the leader using only feedback from its Inertial Measurement Units (IMU). This is accomplished by…