Dynamic Objects Segmentation for Visual Localization in Urban Environments

Visual localization and mapping is a crucial capability to address many challenges in mobile robotics. It constitutes a robust, accurate and cost-effective approach for local and global pose estimation within prior maps. Yet, in highly dynamic environments, like crowded city streets, problems arise as major parts of the image can be covered by dynamic objects. Consequently, visual odometry pipelines often diverge and the localization systems malfunction as detected features are not consistent with the precomputed 3D model. In this work, we present an approach to automatically detect dynamic object instances to improve the robustness of vision-based localization and mapping in crowded environments. By training a convolutional neural network model with a combination of synthetic and real-world data, dynamic object instance masks are learned in a semi-supervised way. The real-world data can be collected with a standard camera and requires minimal further post-processing. Our experiments show that a wide range of dynamic objects can be reliably detected using the presented method. Promising performance is demonstrated on our own and also publicly available datasets, which also shows the generalization capabilities of this approach.Comment: 4 pages, submitted to the IROS 2018 Workshop "From Freezing to Jostling Robots: Current Challenges and New Paradigms for Safe Robot Navigation in Dense Crowds

DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes

The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption limits the use of most visual SLAM systems in populated real-world environments, which are the target of several relevant applications like service robotics or autonomous vehicles. In this paper we present DynaSLAM, a visual SLAM system that, building over ORB-SLAM2 [1], adds the capabilities of dynamic object detection and background inpainting. DynaSLAM is robust in dynamic scenarios for monocular, stereo and RGB-D configurations. We are capable of detecting the moving objects either by multi-view geometry, deep learning or both. Having a static map of the scene allows inpainting the frame background that has been occluded by such dynamic objects. We evaluate our system in public monocular, stereo and RGB-D datasets. We study the impact of several accuracy/speed trade-offs to assess the limits of the proposed methodology. DynaSLAM outperforms the accuracy of standard visual SLAM baselines in highly dynamic scenarios. And it also estimates a map of the static parts of the scene, which is a must for long-term applications in real-world environments.Comment: This work has been accepted at IEEE Robotics and Automation Letters, and will be presented at the IEEE Conference on Intelligent Robots and Systems 201

Non-motor symptom burden in patients with Parkinson's disease with impulse control disorders and compulsive behaviours: results from the COPPADIS cohort.

The study was aimed at analysing the frequency of impulse control disorders (ICDs) and compulsive behaviours (CBs) in patients with Parkinson's disease (PD) and in control subjects (CS) as well as the relationship between ICDs/CBs and motor, nonmotor features and dopaminergic treatment in PD patients. Data came from COPPADIS-2015, an observational, descriptive, nationwide (Spain) study. We used the validated Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) for ICD/CB screening. The association between demographic data and ICDs/CBs was analyzed in both groups. In PD, this relationship was evaluated using clinical features and treatment-related data. As result, 613 PD patients (mean age 62.47 ± 9.09 years, 59.87% men) and 179 CS (mean age 60.84 ± 8.33 years, 47.48% men) were included. ICDs and CBs were more frequent in PD (ICDs 12.7% vs. 1.6%, p < 0.001; CBs 7.18% vs. 1.67%, p = 0.01). PD patients had more frequent previous ICDs history, premorbid impulsive personality and antidepressant treatment (p < 0.05) compared with CS. In PD, patients with ICDs/CBs presented younger age at disease onset, more frequent history of previous ICDs and premorbid personality (p < 0.05), as well as higher comorbidity with nonmotor symptoms, including depression and poor quality of life. Treatment with dopamine agonists increased the risk of ICDs/CBs, being dose dependent (p < 0.05). As conclusions, ICDs and CBs were more frequent in patients with PD than in CS. More nonmotor symptoms were present in patients with PD who had ICDs/CBs compared with those without. Dopamine agonists have a prominent effect on ICDs/CBs, which could be influenced by dose

Non-motor symptom burden in patients with Parkinson's disease with impulse control disorders and compulsive behaviours : results from the COPPADIS cohort

The study was aimed at analysing the frequency of impulse control disorders (ICDs) and compulsive behaviours (CBs) in patients with Parkinson's disease (PD) and in control subjects (CS) as well as the relationship between ICDs/CBs and motor, nonmotor features and dopaminergic treatment in PD patients. Data came from COPPADIS-2015, an observational, descriptive, nationwide (Spain) study. We used the validated Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) for ICD/CB screening. The association between demographic data and ICDs/CBs was analyzed in both groups. In PD, this relationship was evaluated using clinical features and treatment-related data. As result, 613 PD patients (mean age 62.47 ± 9.09 years, 59.87% men) and 179 CS (mean age 60.84 ± 8.33 years, 47.48% men) were included. ICDs and CBs were more frequent in PD (ICDs 12.7% vs. 1.6%, p < 0.001; CBs 7.18% vs. 1.67%, p = 0.01). PD patients had more frequent previous ICDs history, premorbid impulsive personality and antidepressant treatment (p < 0.05) compared with CS. In PD, patients with ICDs/CBs presented younger age at disease onset, more frequent history of previous ICDs and premorbid personality (p < 0.05), as well as higher comorbidity with nonmotor symptoms, including depression and poor quality of life. Treatment with dopamine agonists increased the risk of ICDs/CBs, being dose dependent (p < 0.05). As conclusions, ICDs and CBs were more frequent in patients with PD than in CS. More nonmotor symptoms were present in patients with PD who had ICDs/CBs compared with those without. Dopamine agonists have a prominent effect on ICDs/CBs, which could be influenced by dose