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This paper presents a system for classifying images based on Deep Learning and applied in the recognition of traffic signals aiming to increase road safety increased road safety using autonomous and semi-autonomous intelligent robotic vehicles. This Advanced Driver Assistance System (ADAS) is a system created to automate vehicles, but also to help the human drivers to increase safety and the respect...
This paper presents a path planning system that would enable a robot to navigate through an oil palm plantation. The system is comprised of a distance estimation algorithm, which can accurately identify the location of a detected oil palm tree, an obstacle detection method that accurately detects obstacles and a path planning algorithm which can plan the shortest collision-free path for the robot...
The most recent European and American Roadmaps for robotics point out the role that robotics will play in people's lives in the coming years, constituting an important tool to support everyday life. The main change is associated with a greater proximity and interactivity of robots with people, influencing their lives, such as unmanned vehicles, personal robotics, assistive robotics, etc. Certainly,...
In recent years, service robots have advanced toward having to the ability to move autonomously in an environment in which they co-exist with humans. Thus, the robots must engage in obstacle avoidance to arrive at their goal point. In our previous research, we developed the artificial potential based method that the robot to plans an effective path simulating pedestrian characteristics by gently changing...
The decisional capability of robotic systems has expended significantly in recent years. Their validation typically implies expensive and laborious test campaigns in the field. Part of the validation could use simulation means, but there is currently no systematic method to test robots in virtual worlds. This work aims to provide such a method. We discuss the challenges regarding the definition of...
Recent studies have shown that autistic children tend to speak and interact more with an interactive robot. Unfortunately, due to the high deployment cost, many robotic experiments were still conducted in highly controlled clinical or home settings. Hence, a low cost robot needs to be designed to benefit families with autistic children. In Summer 2014, we have designed a low cost robot, LILI version...
In this paper, an obstacle avoidance strategy using monocular gray-scale robotic vision for turbid water environments is presented. Biologically inspired by the unique vision system of the cubozoan, or box jellyfish, the proposed obstacle avoidance techniques were designed to be as computationally inexpensive as possible for implementation in a compact autonomous underwater vehicle with on-board processing...
Image-guided navigation is an important component of the orthognathic assisted robot, and it allows the robots to operate in precise accordance with a preoperative virtual plan. However, the present commercially available image-guided navigation systems, which use infrared-based tracking, cant guide the relocation of the bone in the orthognathic operation, that means they are not suitable for orthognathic...
In this work we address the problem of autonomous robotic exploration and map building supported by high level information provided by online topological segmentation that incrementally generates an undirected connected graph of the environment. We formulate the exploration problem as the traversal of all the edges of the online graph, being the optimal solution an Eulerian path, if it exist. We propose...
This work addresses a technique for robot motion planning and navigation in dynamic environments. First, a model to represent the future evolution of the moving obstacles in the environment is defined in a robocentric reference, which maps the obstacle motion on the control space, the velocity-time space, of the robot. Second, a planning technique working on that model for navigation and maneuvering...
In this paper we address the problem of online trajectory optimization and cooperative collision avoidance when multiple mobile service robots are operating in close proximity to each other. Using cooperative trajectory optimization to obtain smooth transitions in multi-agent path crossing scenarios applies to the demand for more flexibility and efficiency in industrial autonomous guided vehicle (AGV)...
When remote users share autonomy with a telepresence robot, questions arise as to how the behaviour of the robot is interpreted by local users. We investigated how a robot's violations of social norms under shared autonomy influence the local user's evaluation of the robot's remote users. Specifically, we examined how attribution of such violations to either the robot or the remote user influences...
This paper presents a novel method using accelerated KAZE (AKAZE) and Gist for a context-based semantic classification and recognition of indoor scenes used for a vision-based mobile robot. Our method represents spatial relations among categories for mapping neighborhood units on category maps using counter propagation networks (CPNs) while maintaining sequential information of labels generated from...
Telepresence robots have the potential to improve access to K-12 education for students who are unable to attend school for a variety of reasons. Since previous telepresence research has largely focused on the needs of adult users in workplace settings, it is unknown what challenges must be addressed for these robots to be effective tools in classrooms. In this paper, we seek to better understand...
This paper focuses on requirements for effective human robot collaboration in interactive navigation scenarios. We designed several use-cases where humans and robot had to move in the same environment that resemble canonical path-crossing situations. These use-cases include open as well as constrained spaces. Three different state-of-the-art humanaware navigation planners were used for planning the...
We present DeepNav, a Convolutional Neural Network (CNN) based algorithm for navigating large cities using locally visible street-view images. The DeepNav agent learns to reach its destination quickly by making the correct navigation decisions at intersections. We collect a large-scale dataset of street-view images organized in a graph where nodes are connected by roads. This dataset contains 10 city...
This paper is focused on motion control of a nonholonomic car-like robot. The main idea of the proposed control method is based on an approximate decoupling of phase-constrained kinematics in order to imitate an omnidirectional robot. In order to facilitate the feedback design, the original kinematics is simplified and represented by a nilpotent homogeneous locally equivalent control system. Next,...
This paper makes the focus on the way to increase gradually the autonomy of single vehicle as well as multi-vehicle systems (MVS) to achieve autonomous navigation in complex environments (e.g., cluttered, uncertain and/or dynamic). Its main objective is to give an overview of the developed generic control architectures (mainly decision/action aspects), and their different components, in order to enhance...
The ability to navigate in diverse and previously unknown environments is a critical service of autonomous robots. The validation of the navigation software typically involves test campaigns in the field, which are costly and potentially risky for the robot itself or its environment. An alternative approach is to perform simulation-based testing, by immersing the software in virtual worlds. A question...
Motor relearning after stroke is a lengthy process which should be continued after patients get discharged from the clinic. This project aims at developing a system for telerehabilitation which enables stroke patients to exercise at home autonomously or under supervision of a therapist. The system includes haptic therapy devices which are more promising and beneficial for stroke rehabilitation than...
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