13 accepted papers
Learning-based controllers have achieved impressive performance in agile quadrotor flight but typically rely on massive training in simulation, necessitating accurate system identification for effective Sim2Real transfer. However, even with precise modeling, fixed policies remain susceptible to out-…
This paper introduces LAMM, an open-source framework for large-scale multi-session 3D LiDAR point cloud map merging. LAMM can automatically integrate sub-maps from multiple agents carrying LiDARs with different scanning patterns, facilitating place feature extraction, data association, and global op
Autonomous flight for quadrotors in environments with suddenly appearing objects and disturbances still faces significant challenges. In this work, we propose an integrated planning and control framework called IPC. Specifically, we design a framework consisting of a lightweight frontend and an MPC
Recent advances in LiDAR technology have opened up new possibilities for robotic navigation. Given the widespread use of occupancy grid maps (OGMs) in robotic motion planning, this paper aims to address the challenges of integrating LiDAR with OGMs. To this end, we propose ROG-Map, a uniform grid-ba…
Robot swarms are increasingly being applied in various domains. However, due to the inherent limitation imposed by low real-time communication bandwidth, the synchronization of environmental information among multiple robots remains a persistent and challenging problem in practical applications. In…
Autonomous exploration is a crucial aspect of robotics that has numerous applications. Most of the existing methods greedily choose goals that maximize immediate reward. This strategy is computationally efficient but insufficient for overall exploration efficiency. In recent years, some state-of-the…
Aerial tracking with multiple unmanned aerial vehicles (UAVs) has wide potential in various applications. However, the existing works for swarm tracking typically lack the capability of maintaining high target visibility in cluttered environments. To address this deficiency, we present a decentraliz…
The emergence of low-cost, small form factor and light-weight solid-state LiDAR sensors have brought new opportunities for autonomous unmanned aerial vehicles (UAVs) by advancing navigation safety and computation efficiency. Yet the successful developments of LiDAR-based UAVs must rely on extensive
In this paper, we address the problem of online quadrotor whole-body motion planning (SE(3) planning) in unknown and unstructured environments. We propose a novel multi-resolution search method, which discovers narrow areas requiring full pose planning and normal areas requiring only position planni…
Accurate self and relative state estimation are the critical preconditions for completing swarm tasks, e.g., collaborative autonomous exploration, target tracking, search and rescue. This paper proposes Swarm-LIO: a fully decentralized state estimation method for aerial swarm systems, in which each…
Quadrotors are agile platforms. With human experts, they can perform extremely high-speed flights in cluttered environments. However, fully autonomous flight at high speed remains a significant challenge. In this work, we propose a motion planning algorithm based on the corridor-constrained minimum…
For most LiDAR-inertial odometry, accurate initial states, including temporal offset and extrinsic transfor-mation between LiDAR and 6-axis IMUs, play a significant role and are often considered as prerequisites. However, such information may not be always available in customized LiDAR-inertial syst…
Autonomous delivery of suspended payloads with MAVs has many applications in rescue and logistics transportation. Robust and online estimation of the payload status is important but challenging especially in outdoor environments. The paper develops a novel real-time system for estimating the payload…