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Learning to perform tasks like pulling a door handle or pushing a button, inherently easy for a human, can be surprisingly difficult for a robot. A crucial problem in these kinds of in-contact tasks is the context specificity of pose and force requirements. In this paper, a robot learns in-contact tasks from human kinesthetic demonstrations. To address the need to balance between the position and...
This work proposes a framework that enables arbitrary robots with unknown kinematics models to imitate human demonstrations to acquire a skill, and reproduce it in real-time. The diversity of robots active in non-laboratory environments is growing constantly, and to this end we present an approach for users to be able to easily teach a skill to a robot with any body configuration. Our proposed method...
Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-efficient reinforcement learning framework which enables a robot to learn how to collaborate with a human partner. The robot learns the task from its own sensorimotor experiences in an unsupervised manner.
In this work, we present an approach to learn cost maps for driving in complex urban environments from a large number of demonstrations of human driving behaviour. The learned cost maps are constructed directly from raw sensor measurements, bypassing the effort of manually designing cost maps as well as features. When deploying the cost maps, the trajectories generated not only replicate human-like...
We investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update rate and finite inertia. We implemented two fundamental self-organized algorithms: one with constant direction and one with constant velocity preference to reach a...
A common objective in mobile robotics is to find an optimal trajectory to reach a final destination from a starting point location. Obstacles are likely to be encountered in the robot's trajectory that need to be avoided. In this article, a path planning approach for mobile robots that uses the algorithms of potential field in conjunction with Local Minimal Avoidance (LMA) is presented in order to...
This paper presents a method to determine distance between human operator and SCARA robot using computer vision in order to provide a safe workstation for human robot collaboration. Kinect sensor is used as the input device to the system. Kinect has four streams of data among which depth data is effectively used in this approach. The measured distance is used to calculate danger index. Online trajectory...
Humanoid robot is a dynamic robot which can walk with two legs like a human. Many researchers are interested in this class of robot due to its flexibility in reaching a variety of terrain and also its similarity to humans. The main problem often faced by developers is the motion control system which is rather nontrivial. Having 25 DOF with only two legs, it is difficult to model the robot movement...
The final goal of our research is to develop a rehabilitation support robot for self-standing-up training of hemiplegic stroke patients to restore normal standing-up motion. To improve the motor function of the patient's paralyzed leg, a guided standing-up training is effective. The therapist controls the patient's left/right load balance by pulling or pushing the patient's waist during standing-up...
This paper describes the mechanism of a human-friendly robot. The robot consists of two arms, a body and a mobile base. An air cushion bag is developed to cover the entire exterior of the robot. It can reduce the generated impact forces in a collision between any part of the robot and a human. A passive collision suppression mechanism is also developed to deal with greater impact forces. The suppression...
The main purpose of this paper is to describe the method of group robot control in non-deterministic environments. Here the group structure is proposed for creation with the use of space lattice concept minimizing the computational cost for robot to determine its spatial position in the ranks of the structure. The stages of the solution of two interrelated tasks of robot group motion organization...
In this paper, we present a new approach for dynamic hand gesture recognition that uses intensity, depth, and skeleton joint data captured by Kinect sensor. This method integrates global and local information of a dynamic gesture. First, we represent the skeleton 3D trajectory in spherical coordinates. Then, we select the most relevant points in the hand trajectory with our proposed method for keyframe...
Efficiency and accuracy could be improved by greater degree of automation in underwater tasks operating. However, there is a prerequisite that the manipulator should have a desired end-effector trajectory and suitable force applied to the environment to avoid the possibility of damage to the manipulator, object, or both. To reduce position and orientation deviation of the end-effector of a 7-function...
The advances of information and communication technologies have impacted in control education. Virtual laboratories are increasingly been used to enhance the way that students interact with simulations. High degree of visualization and interaction offered by modern computers open the opportunity to teach theory fundamentals with a more natural approach. This work describes the use of the robot simulator...
In this paper a method is presented that allows an operator to hand-guide a robot along a predefined geometric path. This is a common use case in robot assisted surgery, which often has high demands on precision. In order to ensure the path accuracy of the robot, joint velocity and joint acceleration constraints are enforced to prevent undesired saturation effects of the actuators. Furthermore, necessary...
In this paper we present a neurally plausible model of human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensorimotor interaction of an agent and the world. This model encompasses both learning sensorimotor correlations through motor babbling and also arm motion planning using spreading activation. This model is organized in three layers...
Reliably detecting obstacles and identifying traversable areas is a key challenge in mobile robotics. For redundancy, information from multiple sensors is often fused. In this work we discuss how prior knowledge of the environment can improve the quality of sensor fusion, thereby increasing the performance of an obstacle detection module. We define a methodology to quantify the performance of obstacle...
Robot based rehabilitation is gaining traction also thanks to a generation of light and portable devices. This type of rehabilitation offers a high degree of flexibility in the design of interaction software and therapeutic process. There is therefore the need to perform assessment of the patient upper limb state during and after treatment. This paper presents the integration and fusion of a portable...
We present an active learning architecture that allows a robot to actively learn which data collection strategy is most efficient for acquiring motor skills to achieve multiple outcomes, and generalise over its experience to achieve new outcomes for cumulative learning. In the present work, we consider the learning of tasks that are hierarchically organised, interrelated and more and more difficult...
Acoustic Simultaneous Localization and Mapping (a-SLAM) jointly localizes the trajectory of a microphone array installed on a moving platform, whilst estimating the acoustic map of surrounding sound sources, such as human speakers. Whilst traditional approaches for SLAM in the vision and optical research literature rely on the assumption that the surrounding map features are static, in the acoustic...
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