Robotic bin-picking: Benchmarking robotics grippers with modified YCB object and model set

Robotic bin-picking is increasingly important in the order-picking process in intralogistics. However, many aspects of the robotic bin-picking process (object detection, grasping, manipulation) still require the research community\u27s attention. Established methods are used to test robotic grippers, enabling comparability of the research community\u27s results. This study presents a modified YCB Robotic Gripper Assessment Protocol that was used to evaluate the performance of four robotic grippers (two-fingered, vacuum, gecko, and soft gripper). During the testing, 45 objects from the modified YCB Object and Model Set from the packaging categories, tools, small objects, spherical objects, and deformable objects were grasped and manipulated. The results of the robotic gripper evaluation show that while some robotic grippers performed substantially well, there is an expressive grasp success variation over diverse objects. The results indicate that selecting the object grasp point next to selecting the most suitable robotic gripper is critical in successful object grasping. Therefore, we propose grasp point determination using mechanical software simulation with a model of a two-fingered gripper in an ADAMS/MATLAB co-simulation. Performing software simulations for this task can save time and give comparable results to real-world experiments

A Survey of League Championship Algorithm: Prospects and Challenges

The League Championship Algorithm (LCA) is sport-inspired optimization algorithm that was introduced by Ali Husseinzadeh Kashan in the year 2009. It has since drawn enormous interest among the researchers because of its potential efficiency in solving many optimization problems and real-world applications. The LCA has also shown great potentials in solving non-deterministic polynomial time (NP-complete) problems. This survey presents a brief synopsis of the LCA literatures in peer-reviewed journals, conferences and book chapters. These research articles are then categorized according to indexing in the major academic databases (Web of Science, Scopus, IEEE Xplore and the Google Scholar). The analysis was also done to explore the prospects and the challenges of the algorithm and its acceptability among researchers. This systematic categorization can be used as a basis for future studies.Comment: 10 pages, 2 figures, 2 tables, Indian Journal of Science and Technology, 201

Haptic Shared Control in Tele-Manipulation: Effects of Inaccuracies in Guidance on Task Execution

Haptic shared control is a promising approach to improve tele-manipulated task execution, by making safe and effective control actions tangible through guidance forces. In current research, these guidance forces are most often generated based on pre-generated, errorless models of the remote environment. Hence such guidance forces are exempt from the inaccuracies that can be expected in practical implementations. The goal of this research is to quantify the extent to which task execution is degraded by inaccuracies in the model on which haptic guidance forces are based. In a human-in-the-loop experiment, subjects (n = 14) performed a realistic tele-manipulated assembly task in a virtual environment. Operators were provided with various levels of haptic guidance, namely no haptic guidance (conventional tele-manipulation), haptic guidance without inaccuracies, and haptic guidance with translational inaccuracies (one large inaccuracy, in the order of magnitude of the task, and a second smaller inaccuracy). The quality of natural haptic feedback (i.e., haptic transparency) was varied between high and low to identify the operator\u27s ability to detect and cope with inaccuracies in haptic guidance. The results indicate that haptic guidance is beneficial for task execution when no inaccuracies are present in the guidance. When inaccuracies are present, this may degrade task execution, depending on the magnitude and the direction of the inaccuracy. The effect of inaccuracies on overall task performance is dominated by effects found for the Constrained Translational Movement, due to its potential for jamming. No evidence was found that a higher quality of haptic transparency helps operators to detect and cope with inaccuracies in the haptic guidance.</p

SPATIAL PERCEPTION AND ROBOT OPERATION: THE RELATIONSHIP BETWEEN VISUAL SPATIAL ABILITY AND PERFORMANCE UNDER DIRECT LINE OF SIGHT AND TELEOPERATION

This dissertation investigated the relationship between the spatial perception abilities of operators and robot operation under direct-line-of-sight and teleoperation viewing conditions. This study was an effort to determine if spatial ability testing may be a useful tool in the selection of human-robot interaction (HRI) operators. Participants completed eight cognitive ability measures and operated one of four types of robots under tasks of low and high difficulty. Performance for each participant was tested during both direct-line-of-sight and teleoperation. These results provide additional evidence that spatial perception abilities are reliable predictors of direct-line-of-sight and teleoperation performance. Participants in this study with higher spatial abilities performed faster, with fewer errors, and less variability. In addition, participants with higher spatial abilities were more successful in the accumulation of points. Applications of these findings are discussed in terms of teleoperator selection tools and HRI training and design recommendations with a human-centered design approach