Alignment control using visual servoing and mobilenet single-shot multi-box detection (SSD): a review

The concept is highly critical for robotic technologies that rely on visual feedback. In this context, robot systems tend to be unresponsive due to reliance on pre-programmed trajectory and path, meaning the occurrence of a change in the environment or the absence of an object. This review paper aims to provide comprehensive studies on the recent application of visual servoing and DNN. PBVS and Mobilenet-SSD were chosen algorithms for alignment control of the film handler mechanism of the portable x-ray system. It also discussed the theoretical framework features extraction and description, visual servoing, and Mobilenet-SSD. Likewise, the latest applications of visual servoing and DNN was summarized, including the comparison of Mobilenet-SSD with other sophisticated models. As a result of a previous study presented, visual servoing and MobileNet-SSD provide reliable tools and models for manipulating robotics systems, including where occlusion is present. Furthermore, effective alignment control relies significantly on visual servoing and deep neural reliability, shaped by different parameters such as the type of visual servoing, feature extraction and description, and DNNs used to construct a robust state estimator. Therefore, visual servoing and MobileNet-SSD are parameterized concepts that require enhanced optimization to achieve a specific purpose with distinct tools

Three Dimentional Computer Vision-Based Alternative Control Method for Assistive Robotic Manipulator

JACO (Kinova Technology, Montreal, QC, Canada) is an assistive robotic manipulator that is gaining popularity for its ability to assist individuals with physical impairments in activities of daily living. To accommodate a wider range of user population especially those with severe physical limitations, alternative control methods need to be developed. In this paper, we presented a vision-based assistive robotic manipulation assistance algorithm (AROMA) for JACO, which uses a low-cost 3D depth sensing camera and an improved inverse kinematic algorithm to enable semi-autonomous or autonomous operation of the JACO. The benchtop tests on a series of grasping tasks showed that the AROMA was able to reliably determine target gripper poses. The success rates for the grasping tasks ranged from 85% to 100% for different objects

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

This paper develops a multi-robotic arm system and a stereo vision system to sort objects in the right position according to size and shape attributes. The robotic arm system consists of one master and three slave robots associated with three conveyor belts. Each robotic arm is controlled by a robot controller based on a microcontroller. A master controller is used for the vision system and communicating with slave robotic arms using the Modbus RTU protocol through an RS485 serial interface. The stereo vision system is built to determine the 3D coordinates of the object. Instead of rebuilding the entire disparity map, which is computationally expensive, the centroids of the objects in the two images are calculated to determine the depth value. After that, we can calculate the 3D coordinates of the object by using the formula of the pinhole camera model. Objects are picked up and placed on a conveyor branch according to their shape. The conveyor transports the object to the location of the slave robot. Based on the size attribute that the slave robot receives from the master, the object is picked and placed in the right position. Experiment results reveal the effectiveness of the system. The system can be used in industrial processes to reduce the required time and improve the performance of the production line

Improving the Flexibility and Robustness of Machine Tending Mobile Robots

While traditional manufacturing production cells consist of a fixed base robot repetitively performing tasks, the Industry 5.0 flexible manufacturing cell (FMC) aims to bring Autonomous Industrial Mobile Manipulators (AIMMs) to the factory floor. Composed of a wheeled base and a robot arm, these collaborative robots (cobots) operate alongside people while autonomously performing tasks at different workstations. AIMMs have been tested in real production systems, but the development of the control algorithms necessary for automating a robot that is a combination of two cobots remains an open challenge before the large scale adoption of this technology occurs in industry. Currently popular docking based methods require a mount point for the docking station and considerable time for the robot to locate and park. These limitations necessitate the consideration and implementation of more modern robot control and path planning techniques. This work proposes and implements a simulation testbed that uses a contemporary whole-body control, OCS2, to perform more flexible pick-and-place tasks. Within this testbed, an Industry 5.0 based pick-and-place framework is deployed, fine-tuned and tested. This system supports the one-shot lead-through based assignment of a prepick position by an operator, thus enabling the cobot to drive to this position and successfully pick up the part agnostic of base orientation and/or position. The proposed system allows robot path planning experimentation and assessment against a variety of cost and constraint values, and is capable of being modified to support various vision based part locating algorithms

Kinematically-Decoupled Impedance Control for Fast Object Visual Servoing and Grasping on Quadruped Manipulators

We propose a control pipeline for SAG (Searching, Approaching, and Grasping) of objects, based on a decoupled arm kinematic chain and impedance control, which integrates image-based visual servoing (IBVS). The kinematic decoupling allows for fast end-effector motions and recovery that leads to robust visual servoing. The whole approach and pipeline can be generalized for any mobile platform (wheeled or tracked vehicles), but is most suitable for dynamically moving quadruped manipulators thanks to their reactivity against disturbances. The compliance of the impedance controller makes the robot safer for interactions with humans and the environment. We demonstrate the performance and robustness of the proposed approach with various experiments on our 140 kg HyQReal quadruped robot equipped with a 7-DoF manipulator arm. The experiments consider dynamic locomotion, tracking under external disturbances, and fast motions of the target object.Comment: Accepted as contributed paper at 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023

Independence in the Home: A Wearable Interface for a Person with Quadriplegia to Teleoperate a Mobile Manipulator

Teleoperation of mobile manipulators within a home environment can significantly enhance the independence of individuals with severe motor impairments, allowing them to regain the ability to perform self-care and household tasks. There is a critical need for novel teleoperation interfaces to offer effective alternatives for individuals with impairments who may encounter challenges in using existing interfaces due to physical limitations. In this work, we iterate on one such interface, HAT (Head-Worn Assistive Teleoperation), an inertial-based wearable integrated into any head-worn garment. We evaluate HAT through a 7-day in-home study with Henry Evans, a non-speaking individual with quadriplegia who has participated extensively in assistive robotics studies. We additionally evaluate HAT with a proposed shared control method for mobile manipulators termed Driver Assistance and demonstrate how the interface generalizes to other physical devices and contexts. Our results show that HAT is a strong teleoperation interface across key metrics including efficiency, errors, learning curve, and workload. Code and videos are located on our project website

Towards automated sample collection and return in extreme underwater environments

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Billings, G., Walter, M., Pizarro, O., Johnson-Roberson, M., & Camilli, R. Towards automated sample collection and return in extreme underwater environments. Journal of Field Robotics, 2(1), (2022): 1351–1385, https://doi.org/10.55417/fr.2022045.In this report, we present the system design, operational strategy, and results of coordinated multivehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of remotely operated vehicle (ROV) manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an analog to a planetary lander, which must be capable of high-level autonomy. Our field trials involve two underwater vehicles, the SuBastian ROV and the Nereid Under Ice (NUI) hybrid ROV for mixed initiative (i.e., teleoperated or autonomous) missions, both equipped seven-degrees-of-freedom hydraulic manipulators. We describe an adaptable, hardware-independent computer vision architecture that enables high-level automated manipulation. The vision system provides a three-dimensional understanding of the workspace to inform manipulator motion planning in complex unstructured environments. We demonstrate the effectiveness of the vision system and control framework through field trials in increasingly challenging environments, including the automated collection and return of biological samples from within the active undersea volcano Kolumbo. Based on our experiences in the field, we discuss the performance of our system and identify promising directions for future research.This work was funded under a NASA PSTAR grant, number NNX16AL08G, and by the National Science Foundation under grants IIS-1830660 and IIS-1830500. The authors would like to thank the Costa Rican Ministry of Environment and Energy and National System of Conservation Areas for permitting research operations at the Costa Rican shelf margin, and the Schmidt Ocean Institute (including the captain and crew of the R/V Falkor and ROV SuBastian) for their generous support and making the FK181210 expedition safe and highly successful. Additionally, the authors would like to thank the Greek Ministry of Foreign Affairs for permitting the 2019 Kolumbo Expedition to the Kolumbo and Santorini calderas, as well as Prof. Evi Nomikou and Dr. Aggelos Mallios for their expert guidance and tireless contributions to the expedition