Navigation safety is critical for many autonomous systems such as self-driving vehicles in an urban environment. It requires an explicit consideration of boundary constraints that describe the borders of any infeasible, non-navigable, or unsafe regions. ...

Semi-autonomous aircraft navigation is a high-risk domain where confidence on the prediction is required. For that, this paper introduces the use of conformal predictions strategies for regression problems. While standard approaches use an ...

The Inter-Satellite Link (ISL) technology plays a vital role in BeiDou Navigation Satellite System (BDS), and it’s a developmental trend of the future GNSS. However, ISL is insensitive to both the Earth’s rotation and the constellation’s overall ...

This article introduces a novel Deep Reinforcement Learning (DRL)-based approach for mapless navigation in Industrial Autonomous Mobile Robots, emphasizing advancements in generalization through Potential Risk State Augmentation (PRSA) and an ...

Autonomous navigation and information gathering in challenging environments are demanding since the robot’s sensors may be susceptible to non-negligible noise, its localization and mapping may be subject to significant uncertainty and drift, and ...

Reinforcement learning (RL) and imitation learning (IL) are quite two useful machine learning techniques that were shown to be potential in enhancing navigation performance. Basically, both of these methods try to find a policy decision function ...

Due to random sampling and the unpredictability of moving obstacles, it remains challenging for mobile robots to effectively learn navigation policies and accomplish obstacle avoidance safely. Overcoming such challenges can reduce the time cost ...

Unmanned aerial vehicles (UAVs) are a valuable source of data for a wide range of real-time applications, due to their functionality, availability, adaptability, and maneuverability. Working as mobile sensors, they can provide a cost-effective ...

Recently, camera-based approaches have been proposed to replace expensive LiDAR or real-time kinematic (RTK) based solutions for the unmanned tractors operating in an orchard-like environment. However, constructing a completely autonomous ...

• Multi-task neural network for trunk, obstacle, and traversable area detection.
• Frame transformation algorithm for perception results downsizing and transformation.
• Motion planning module for global path planning and control ...

• Proposing a CSP attention block to achieve feature enhancement.
• A fast receptive field expansion module is designed to expand feature receptive field.
• An adaptively spatial feature fusion module is introduced to implement feature ...

Autonomous navigation of agricultural devices plays an indispensable step for the realization of various field intelligent operation tasks. However, the accurate extraction of navigation path is still a challenging task due to the complex orchard ...

• This paper presents a novel one-shot domain adaptive real-time 3D detection method that addresses the challenge of insufficient target domain samples by designing a semantic-geometry-intensity space generator. This generator learns both ...

By introducing deep learning, LiDAR-based solutions have achieved impressive accuracy in 3D obstacle detection. However, gathering and labeling sufficient samples is the precondition for the effectiveness of existing solutions. This precondition ...

Crop row detection is the basis for the visual navigation of agricultural machinery. Previous research has typically developed crop detection schemes based on specific application objects, with cumbersome image processing steps. A ...

Nowadays, most agricultural robots rely on precise and expensive localisation, typically based on global navigation satellite systems (GNSS) and real-time kinematic (RTK) receivers. Unfortunately, the precision of GNSS localisation ...

• We extend the classic visual teach & repeat to a novel teach & generalise approach.

This paper proposes an environment perception algorithm based on the principle of vanishing point in perspective projection and a cascaded multi-variable RBF neural network PID adaptive control method to address the drawbacks of the existing indoor ...

Display Omitted

• A method for hybrid rice row detection during pollination is proposed.
• Unlabelled images are used to improved hybrid rice row detection accuracy.
• A semi-supervised model incorporating multi-perturbations is developed.

Autonomous navigation of the hybrid rice pollination process is essential to increasing seed production. Detecting crop rows in real-time with flexible and cost-effective machine vision equipment is crucial to achieving autonomous navigation. The ...

Maritime Autonomous Surface Ships (MASS) have obtained wide attention in recent years, which is relied on their attractive socio-economic benefits and potential to improve safety. One of the main characteristics of MASS is that it can ...

This paper focuses on inverse reinforcement learning for autonomous navigation using distance and semantic category observations. The objective is to infer a cost function that explains demonstrated behavior while relying only on the expert’s ...

Lumen is a common anatomical condition in endoscopic therapy or diagnostics. The navigation of autonomous robotic endoscopy usually involves vision techniques such as detection of lumen center or anatomically specific contour features. ...

• Use explicit and implicit geometric consistency for endoscopic depth estimation.

Reliable knowledge of the vehicle heading plays a significant role in the autonomous navigation of agricultural Unmanned Ground Vehicles (UGVs), especially in the context of unstructured outdoor environments such as rural and forestry ...

• Increasing the accuracy of GPS-based heading estimation.
• Autonomous mobile ...

Conflict prediction is a vital component of path planning for autonomous vehicles. Prediction methods must be accurate for reliable navigation, but also computationally efficient to enable online path planning. Efficient prediction methods are ...