The concept of controlling a wheelchair using brain signals is promising. However, the continuous control of a wheelchair based on unstable and noisy electroencephalogram signals is unreliable and generates a significant mental burden for the user. A feasible solution is to integrate a brain–computer interface (BCI) with automated navigation techniques. This paper presents a brain-controlled intelligent wheelchair with the capability of automatic navigation. Using an autonomous navigation system, candidate destinations and waypoints are automatically generated based on the existing environment. The user selects a destination using a motor imagery (MI)-based or P300-based BCI. According to the determined destination, the navigation system plans a short and safe path and navigates the wheelchair to the destination. During the movement of the wheelchair, the user can issue a stop command with the BCI. Using our system, the mental burden of the user can be substantially alleviated. Furthermore, our system can adapt to changes in the environment. Two experiments based on MI and P300 were conducted to demonstrate the effectiveness of our system.

Control of a Wheelchair in an Indoor Environment Based on a Brain–Computer Interface and Automated Navigation

This paper presents a complete review of computer vision algorithms and vision-based intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles (UAVs) in the latest decade. During this time, the evolution of relevant technologies for UAVs; such as component miniaturization, the increase of computational capabilities, and the evolution of computer vision techniques have allowed an important advance in the development of UAVs technologies and applications. Particularly, computer vision technologies integrated in UAVs allow to develop cutting-edge technologies to cope with aerial perception difficulties; such as visual navigation algorithms, obstacle detection and avoidance and aerial decision-making. All these expert technologies have developed a wide spectrum of application for UAVs, beyond the classic military and defense purposes. Unmanned Aerial Vehicles and Computer Vision are common topics in expert systems, so thanks to the recent advances in perception technologies, modern intelligent applications are developed to enhance autonomous UAV positioning, or automatic algorithms to avoid aerial collisions, among others. Then, the presented survey is based on artificial perception applications that represent important advances in the latest years in the expert system field related to the Unmanned Aerial Vehicles. In this paper, the most significant advances in this field are presented, able to solve fundamental technical limitations; such as visual odometry, obstacle detection, mapping and localization, et cetera. Besides, they have been analyzed based on their capabilities and potential utility. Moreover, the applications and UAVs are divided and categorized according to different criteria.

Survey of computer vision algorithms and applications for unmanned aerial vehicles

Over the past decades, many robots for the elderly have been developed, supporting different activities of elderly people. A systematic review in four scientific literature databases and a search in article references and European projects was performed in order to create an overview of robots supporting independent living of elderly people. The robots found were categorized based on their development stage, the activity domains they claim to support, and the type of support provided (i.e., physical, non-physical, and/or non-specified). In total, 107 robots for the elderly were identified. Six robots were still in a concept phase, 95 in a development phase, and six of these robots were commercially available. These robots claimed to provide support related to four activity domains: mobility, self-care, interpersonal interaction & relationships, and other activities. Of the many robots developed, only a small percentage is commercially available. Technical ambitions seem to be guiding robot development. To prolong independent living, the step towards physical support is inevitable and needs to be taken. However, it will be a long time before a robot will be capable of supporting multiple activities in a physical manner in the home of an elderly person in order to enhance their independent living.

Overview and Categorization of Robots Supporting Independent Living of Elderly People: What Activities Do They Support and How Far Have They Developed

In recent years, with the current advancements in Robotics and Artificial Intelligence (AI), robots have the potential to support the field of healthcare. Robotic systems are often introduced in the care of the elderly, children, and persons with disabilities, in hospitals, in rehabilitation and walking assistance, and other healthcare situations. In this survey paper, the recent advances in robotic technology applied in the healthcare domain are discussed. The paper provides detailed information about state-of-the-art research in care, hospital, assistive, rehabilitation, and walking assisting robots. The paper also discusses the open challenges healthcare robots face to be integrated into our society.

A Survey of Robots in Healthcare

Mobile robots can complete a task in cooperation with a human partner. In this letter, a hybrid shared control method for a mobile robot with omnidirectional wheels is proposed. A human partner utilizes a six degrees of freedom haptic device and electromyography (EMG) signals sensor to control the mobile robot. A hybrid shared control approach based on EMG and artificial potential field is exploited to avoid obstacles according to the repulsive force and attractive force and to enhance the human perception of the remote environment based on force feedback of the mobile platform. This shared control method enables the human partner to tele-control the mobile robot's motion and achieve obstacles avoidance synchronously. Compared with conventional shared control methods, this proposed one provides a force feedback based on muscle activation and drives the human partners to update their control intention with predictability. Experimental results demonstrate the enhanced performance of the mobile robots in comparison with the methods in the literature.

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A Teleoperation Framework for Mobile Robots Based on Shared Control

This paper presents a CAD-based six-degrees-of-freedom (6-DoF) pose estimation design for random bin picking for multiple objects. A virtual camera generates a point cloud database for the objects using their 3D CAD models. To reduce the computational time of 3D pose estimation, a voxel grid filter reduces the number of points for the 3D cloud of the objects. A voting scheme is used for object recognition and to estimate the 6-DoF pose for different objects. An outlier filter filters out badly matching poses so that the robot arm always picks up the upper object in the bin, which increases the success rate. In a computer simulation using a synthetic scene, the average recognition rate is 97.81 % for three different objects with various poses. A series of experiments have been conducted to validate the proposed method using a Kuka robot arm. The average recognition rate for three objects is 92.39 % and the picking success rate is 89.67 %.

CAD-based Pose Estimation Design for Random Bin Picking using a RGB-D Camera

This brief presents a control design for a walking-assistant robot in a complex indoor environment, such that it can assist a walking-impaired person to walk and avoid unexpected obstacles. In this design, the robot motion is a resultant of autonomous navigation and compliant motion control. The compliance motion controller allows the robot to possess passive behavior following the motion intent of the user, while the autonomous guidance gives safe navigation of the robot without colliding with any obstacles. A shared-control approach is suggested to combine the passive compliant behavior and safe guidance of the robot. When a user exerts force to the robot, the mobile platform responds to adjust the speed in compliance with the user movement. On the other hand, the autonomous navigation controller is designed to provide collision-free guidance. Using the developed shared controller, outputs of the compliance motion controller and autonomous navigation controller are fused to generate appropriate motion for the robot. In this manner, passive behavior allows the walking-assistant robot to adapt to a user’s motion intent and move in compliance with user. Meanwhile, the active guidance adjusts the linear velocity and the direction of the robot in real time in response to the environmental data received from the on-board laser scanner. The developed algorithms have been implemented on a self-constructed walking-assistant robot. Experimental results validate the proposed design and demonstrate that the robot can actively avoid unexpected obstacles while move passively following the user to the destination.

Shared Control Design of a Walking-Assistant Robot

This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. An image processing procedure is developed to estimate distances between the robot and obstacles based-on inverse perspective transformation (IPT) in image plane. A robust image processing solution is proposed to detect and segment navigatable ground plane area within the camera view. The proposed method integrate robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, a result similar to the occupancy grid map is obtained for mobile robot obstacle avoidance and navigation. Practical experimental results of a wheeled mobile robot show that the proposed imaging system successfully estimates distance of objects and avoid obstacles in an indoor environment.

Robust ground plane detection for obstacle avoidance of mobile robots using a monocular camera

This paper presents a shared-control-based design for teleoperation of a dual-arm omnidirectional mobile robot—a robot that can execute tasks commanded by a remotely user, or that can operate autonomously by adapting to its immediate environment, or that can operate in both modes simultaneously. To achieve this capability for the robot and for its effective remote control, a shared-control method has been developed. The controller determines the control gains for both the human and the autonomous commands by computing the user's confidence factor. For ease of use, a smartphone/tablet is used to control the robot. Using this approach, the robot allows the user to manipulate its motion from a remote site and compensates for a lack of local human knowledge. Practical experiments validate the proposed design and demonstrate the potential of the proposed shared-control method for home-service tasks.

Interactive Teleoperation of a Mobile Manipulator Using a Shared-Control Approach

In this paper, we propose a CAD-based 6-DOF pose estimation design for random bin-picking of multiple different objects using a Kinect RGB-D sensor. 3D CAD models of objects are constructed via a virtual camera, which generates a point cloud database for object recognition and pose estimation. A voxel grid filter is suggested to reduce the number of 3D point cloud of objects for reducing computing time of pose estimation. A voting-scheme method was adopted for the 6-DOF pose estimation a swell as object recognition of different type objects in the bin. Furthermore, an outlier filter is designed to filter out bad matching poses and occluded ones, so that the robot arm always picks up the upper object in the bin to increase pick up success rate. A series of experiments on a Kuka 6-axis robot revels that the proposed system works satisfactorily to pick up all random objects in the bin. The average recognition rate of three different type objects is 93.9% and the pickup success rate is 89.7%.

Sin-Yi Jiang

Papers

CAD-based Pose Estimation Design for Random Bin Picking using a RGB-D Camera

Shared Control Design of a Walking-Assistant Robot

Robust ground plane detection for obstacle avoidance of mobile robots using a monocular camera

Interactive Teleoperation of a Mobile Manipulator Using a Shared-Control Approach

CAD-based pose estimation for random bin-picking of multiple objects using a RGB-D camera