SEER: Safe efficient exploration for aerial robots using learning to predict information gain
We address the problem of efficient 3-D exploration in indoor environments for micro aerial
vehicles with limited sensing capabilities and payload/power constraints. We develop an …
vehicles with limited sensing capabilities and payload/power constraints. We develop an …
Enhancing robot task completion through environment and task inference: A survey from the mobile robot perspective
In real-world environments, ranging from urban disastrous scenes to underground mining
tunnels, autonomous mobile robots are being deployed in harsh and cluttered …
tunnels, autonomous mobile robots are being deployed in harsh and cluttered …
Monoocc: Digging into monocular semantic occupancy prediction
Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and
semantic information of scenes from only 2D images. It has garnered significant attention …
semantic information of scenes from only 2D images. It has garnered significant attention …
Uncertainty-aware visually-attentive navigation using deep neural networks
Autonomous navigation and information gathering in challenging environments are
demanding since the robot's sensors may be susceptible to non-negligible noise, its …
demanding since the robot's sensors may be susceptible to non-negligible noise, its …
Occlusion-aware crowd navigation using people as sensors
Autonomous navigation in crowded spaces poses a challenge for mobile robots due to the
highly dynamic, partially observable environment. Occlusions are highly prevalent in such …
highly dynamic, partially observable environment. Occlusions are highly prevalent in such …
Virtual surfaces and attitude aware planning and behaviours for negative obstacle navigation
This letter presents an autonomous navigation system for ground robots traversing
aggressive unstructured terrain through a cohesive arrangement of mapping, deliberative …
aggressive unstructured terrain through a cohesive arrangement of mapping, deliberative …
Train here, drive there: ROS based end-to-end autonomous-driving pipeline validation in CARLA simulator using the NHTSA typology
C Gómez-Huélamo, J Del Egido, LM Bergasa… - Multimedia Tools and …, 2022 - Springer
Urban complex scenarios are the most challenging situations in the field of Autonomous
Driving (AD). In that sense, an AD pipeline should be tested in countless environments and …
Driving (AD). In that sense, an AD pipeline should be tested in countless environments and …
Make it dense: Self-supervised geometric scan completion of sparse 3d lidar scans in large outdoor environments
Mapping systems that turn sensor data into a model of the environment are standard
components in mobile robotics. Outdoor robots are often equipped with 3D LiDAR sensors …
components in mobile robotics. Outdoor robots are often equipped with 3D LiDAR sensors …
[HTML][HTML] D+∗: A risk aware platform agnostic heterogeneous path planner
S Karlsson, A Koval, C Kanellakis… - Expert systems with …, 2023 - Elsevier
This article establishes the novel D+∗, a risk-aware and platform-agnostic heterogeneous
global path planner for robotic navigation in complex environments. The proposed planner …
global path planner for robotic navigation in complex environments. The proposed planner …
Reinforcement learning for collision-free flight exploiting deep collision encoding
M Kulkarni, K Alexis - arXiv preprint arXiv:2402.03947, 2024 - arxiv.org
This work contributes a novel deep navigation policy that enables collision-free flight of
aerial robots based on a modular approach exploiting deep collision encoding and …
aerial robots based on a modular approach exploiting deep collision encoding and …