Present and future of slam in extreme environments: The darpa subt challenge
This article surveys recent progress and discusses future opportunities for simultaneous
localization and map** (SLAM) in extreme underground environments. SLAM in …
localization and map** (SLAM) in extreme underground environments. SLAM in …
Present and future of slam in extreme underground environments
This paper reports on the state of the art in underground SLAM by discussing different SLAM
strategies and results across six teams that participated in the three-year-long SubT …
strategies and results across six teams that participated in the three-year-long SubT …
Introspection of 2d object detection using processed neural activation patterns in automated driving systems
While deep neural network (DNN) models have become extremely popular for object
detection in automated driving systems (ADS), the dynamic and varied nature of the road …
detection in automated driving systems (ADS), the dynamic and varied nature of the road …
Introspection of dnn-based perception functions in automated driving systems: State-of-the-art and open research challenges
Automated driving systems (ADSs) aim to improve the safety, efficiency and comfort of future
vehicles. To achieve this, ADSs use sensors to collect raw data from their environment. This …
vehicles. To achieve this, ADSs use sensors to collect raw data from their environment. This …
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Monitoring the integrity of object detection for errors within the perception module of
automated driving systems (ADS) is paramount for ensuring safety. Despite recent …
automated driving systems (ADS) is paramount for ensuring safety. Despite recent …
How safe is particle filtering-based localization for mobile robots? An integrity monitoring approach
Deriving safe bounds on particle filter estimate is a research problem that, if solved, could
greatly benefit robots in life-critical applications, a field that is facing increasing interest as …
greatly benefit robots in life-critical applications, a field that is facing increasing interest as …
Run-time introspection of 2d object detection in automated driving systems using learning representations
Reliable detection of various objects and road users in the surrounding environment is
crucial for the safe operation of automated driving systems (ADS). Despite recent progresses …
crucial for the safe operation of automated driving systems (ADS). Despite recent progresses …
Task-aware risk estimation of perception failures for autonomous vehicles
Safety and performance are key enablers for autonomous driving: on the one hand we want
our autonomous vehicles (AVs) to be safe, while at the same time their performance (eg …
our autonomous vehicles (AVs) to be safe, while at the same time their performance (eg …
VERF: Runtime Monitoring of Pose Estimation with Neural Radiance Fields
We present VERF, a collection of two methods (VERF-PnP and VERF-Light) for providing
runtime assurance on the correctness of a camera pose estimate of a monocular camera …
runtime assurance on the correctness of a camera pose estimate of a monocular camera …
When Is It Likely to Fail? Performance Monitor for Black-Box Trajectory Prediction Model
Accurate trajectory prediction is vital for various applications, including autonomous
vehicles. However, the complexity and limited transparency of many prediction algorithms …
vehicles. However, the complexity and limited transparency of many prediction algorithms …