Controlling a remotely located Robot using Hand Gestures in real time: A DSP implementation

Telepresence is a necessity for present time as we can't reach everywhere and also it is useful in saving human life at dangerous places. A robot, which could be controlled from a distant location, can solve these problems. This could be via communication waves or networking methods. Also controlling should be in real time and smooth so that it can actuate on every minor signal in an effective way. This paper discusses a method to control a robot over the network from a distant location. The robot was controlled by hand gestures which were captured by the live camera. A DSP board TMS320DM642EVM was used to implement image pre-processing and fastening the whole system. PCA was used for gesture classification and robot actuation was done according to predefined procedures. Classification information was sent over the network in the experiment. This method is robust and could be used to control any kind of robot over distance

A real-time human-robot interaction system based on gestures for assistive scenarios

Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system — which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops — is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times.Postprint (author's final draft

Contactless medium scale industrial robot collaboration

The growing cost of High-Value/Mix and Low Volume (HMLV) industries like Aerospace is heavily based on industrial robots and manual operations done by operators [1]. Robots are excellent in repeatability by HMLV industries need changes with every single product. On the other hand human workforce is good at variability and intelligence but cost a lot as production rate is not comparable to robots and machines. There are flexible systems which have been specifically introduced for this type of industry FLEXA is one of them. But still there is need of collaboration between human and robot to get the flexible and cost effective solution [2]. A comprehensive survey has been conducted specifically on the issue of Human Robot collaboration [3] which laid out many advantages of this approach includes flexibility, cost-effectiveness and use of robot as intelligent assistant. There are several attempts have been made for Human Robot Collaboration for HMLV industry and Chen et al. attempt is one of them

Intention recognition for gaze controlled robotic minimally invasive laser ablation

Eye tracking technology has shown promising results for allowing hands-free control of robotically-mounted cameras and tools. However existing systems present only limited capabilities in allowing the full range of camera motions in a safe, intuitive manner. This paper introduces a framework for the recognition of surgeon intention, allowing activation and control of the camera through natural gaze behaviour. The system is resistant to noise such as blinking, while allowing the surgeon to look away safely at any time. Furthermore, this paper presents a novel approach to control the translation of the camera along its optical axis using a combination of eye tracking and stereo reconstruction. Combining eye tracking and stereo reconstruction allows the system to determine which point in 3D space the user is fixating, enabling a translation of the camera to achieve the optimal viewing distance. In addition, the eye tracking information is used to perform automatic laser targeting for laser ablation. The desired target point of the laser, mounted on a separate robotic arm, is determined with the eye tracking thus removing the need to manually adjust the laser's target point before starting each new ablation. The calibration methodology used to obtain millimetre precision for the laser targeting without the aid of visual servoing is described. Finally, a user study validating the system is presented, showing clear improvement with median task times under half of those of a manually controlled robotic system