Reinforcement Learning-Based Assistive Framework for Disabled Persons

Robot programming by demonstration (PbD) enables human users to teach the robot and increases its capabilities by interactive teaching without having to manually program the robot. PbD combined with intelligent machine learning algothrims can help us to develop autonomous robots for various industrial and domestic tasks. One such task is the pouring of liquids from bottle into the cup/glass. In this paper the first step is to teach the robot liquid pouring task by the human user in order to facilitate physically disabled people in making various types of drinks and then dataset is created from the user taken demonstrations. In training stage the dataset obtained is feed to the decision-making algorithm based on reinforcement learning. The algorithm enables the robot to learn to pour different liquids under different pouring conditions with the help of minimum number of human user demonstrations needed for the learning of task. The acquired results show that the robot can learn to pour different liquids and is able to accurately adapt to different pouring conditions by using reward-based system and online feedback. Furthermore the results show that the proposed framework can work with different types of liquid and container sizes without any further need for reprogramming or demonstrations.

Industrial robot programming by demonstration using stereoscopic vision and inertial sensing

Purpose The purpose of this paper is to present a programming by demonstration (PbD) system based on 3D stereoscopic vision and inertial sensing that provides a cost-effective pose tracking system, even during error-prone situations, such as camera occlusions. Design/methodology/approach The proposed PbD system is based on the 6D Mimic innovative solution, whose six degrees of freedom marker hardware had to be revised and restructured to accommodate an IMU sensor. Additionally, a new software pipeline was designed to include this new sensing device, seeking the improvement of the overall system’s robustness in stereoscopic vision occlusion situations. Findings The IMU component and the new software pipeline allow the 6D Mimic system to successfully maintain the pose tracking when the main tracking tool, i.e. the stereoscopic vision, fails. Therefore, the system improves in terms of reliability, robustness, and accuracy which were verified by real experiments. Practical implications Based on this proposal, the 6D Mimic system reaches a reliable and low-cost PbD methodology. Therefore, the robot can accurately replicate, on an industrial scale, the artisan level performance of highly skilled shop-floor operators. Originality/value To the best of the authors’ knowledge, the sensor fusion between stereoscopic images and IMU applied to robot PbD is a novel approach. The system is entirely designed aiming to reduce costs and taking advantage of an offline processing step for data analysis, filtering and fusion, enhancing the reliability of the PbD system.

Development and evaluation of demonstration information recording approach for wheelchair mounted robotic arm

To offer simple and convenient assistance for the elderly and disabled, researchers focus on programming by demonstration approach to improve the intelligence and adaptability of wheelchair mounted robotic arm assistive robot. But how to easily and quickly obtain the demonstration information is still an urgent problem to be solved. Based on the systematic analysis of the daily living tasks in need of robot assistance, this paper proposes the key-point-based programming by demonstration recording approach to quickly obtain the demonstration information and develops a specified demonstration interface to simplify the operation process. A corresponding evaluation approach is also proposed from the demonstration trajectories and demonstration process two aspects. Additionally, tasks of “holding water glass task”, “eating task”, and “opening door task” are carried out and experimental results, as well as comparative evaluations confirm the validity of the proposed approach with high efficiency. This study can not only offer a convenient and feasible way to obtain the demonstration information of daily living tasks, but also lay a good foundation for the assistive robot to learn relative motion skills, especially for the demonstrated dexterous manipulation skills, and semi-autonomously accomplish complex, multi-step tasks following the user’s instructions in the daily home environment.

Generating Block-Structured Parallel Process Models by Demonstration

Programming by demonstration (PBD) is a technique which allows end users to create, modify, accommodate, and expand programs by demonstrating what the program is supposed to do. Although the ideal of common-purpose programming by demonstration or by examples has been rejected as practically unrealistic, this approach has found its application and shown potentials when limited to specific narrow domains and ranges of applications. In this paper, the original method of applying the principles of programming by demonstration in the area of process mining (PM) to interactive construction of block-structured parallel business processes models is presented. A technique and tool that enable interactive process mining and incremental discovery of process models have been described in this paper. The idea is based on the following principle: using a demonstrational user interface, a user demonstrates scenarios of execution of parallel business process activities, and the system gives a generalized model process specification. A modified process mining technique with the α|| algorithm applied on weakly complete event logs is used for creating parallel business process models using demonstration.