On the guidance, navigation and control of in-orbit space robotic missions: A survey and prospective vision

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is characterized by the degeneration of both upper and lower motor neurons, which leads to muscle weakness and subsequently paralysis. It begins subtly with focal weakness but spreads relentlessly to involve most muscles, thus proving to be effectively incurable. Typically, death due to respiratory paralysis occurs in 3–5 years. To date, it has been shown that the management of ALS patients is best achieved with a multidisciplinary approach, and with the help of emerging technologies ranging from multidisciplinary teleconsults (for monitoring the dysphagia, respiratory function, and nutritional status) to brain-computer interfaces and eye tracking for alternative augmentative communication, until robotics, it may increase effectiveness. The COVID-19 pandemic created a spasmodic need to accelerate the development and implementation of such technologies in clinical practice, to improve the daily lives of both ALS patients and caregivers. However, despite the remarkable strides that have been made in the field, there are still issues to be addressed. This review will be discussed on the eureka moment of emerging technologies for ALS, used as a blueprint not only for neurodegenerative diseases, examining the current technologies already in place or being evaluated, highlighting the pros and cons for future clinical applications. 

https://link.springer.com/content/pdf/10.1007/s00415-022-10971-w.pdf

Emerging technologies for management of patients with amyotrophic lateral sclerosis: from telehealth to assistive robotics and neural interfaces

This paper considers basket grasps, where a two-finger robot hand forms a basket that can safely lift and carry rigid objects in a 2-D gravitational environment. The two-finger basket grasps form special points in a high-dimensional configuration space of the object and two-finger robot hand. This paper establishes that all two-finger basket grasps can be found in a low-dimensional contact space that parametrizes the two-finger contacts along the supported object boundary. Using contact space, each basket grasp is associated with its depth that provides a security measure while carrying the object, as well as its safety margin away from a critical finger opening where the object drops-off into its intended destination. Geometric techniques that compute the depth and drop-off finger opening are described and illustrated with detailed graphical and numerical examples.

Geometric Characterization of Two-Finger Basket Grasps of 2-D Objects: Contact Space Formulation

We propose a geometry-based grasping method for vine tomatoes. It relies on a computer-vision pipeline to identify the required geometric features of the tomatoes and of the truss stem. The grasping method then uses a geometric model of the robotic hand and the truss to determine a suitable grasping location on the stem. This approach allows for grasping tomato trusses without requiring delicate contact sensors or complex mechanistic models and under minimal risk of damaging the tomatoes. Lab experiments were conducted to validate the proposed methods, using an RGB-D camera and a low-cost robotic manipulator. The success rate was 83% to 92%, depending on the type of truss.

Geometry-Based Grasping of Vine Tomatoes.

Abstract In recent years, the removal of orbital debris has become an increasingly urgent task due to advancements in human space exploration. Capturing space debris through caging manipulation offers notable advantages in terms of robustness and controllability. This paper proposes a configuration-based caging manipulation design method for a cable-driven flexible arm. First, the cable-driven flexible arm with multi self-lockable links is introduced. To quantify the caging configurations formed by different self-lockable link selections, a novel planar caging quality metric is then presented for arbitrary planar objects. Using this metric, a caging design method is developed for the flexible arm to conduct caging manipulations. Finally, the caging manipulation strategies are discussed with lock selection maps for different objects, and a robust caging strategy considering uncertainty is further explored. Simulation and experimental results validate the effectiveness of the proposed caging design method and demonstrate better performance compared to conventional caging methods.

Configuration-based caging manipulation design for a cable-driven flexible arm with multi self-lockable links

In this paper, we present a novel method for caging-based grasping of deformable objects. This method enables manipulators to grasp objects simply with geometric constraints by using position control of robotic hands, and not through force controls or mechanical analysis. Therefore, this method has cost benefits and algorithmic simplicity. In our previous studies, we mainly focused on caging-based grasping of rigid objects such as 2D/3D primitive-shaped objects. However, considering realistic objects, manipulation of deformable objects is also required frequently. Hence, this study is motivated to manipulate deformable objects, adopting a caging-based grasping approach. We formulate caging-based grasping of deformable objects, and target three types of deformable objects: a rigid object covered with a soft part, a closed-loop structure, and two rigid bodies connected with a string, which can be regarded as primitive shapes. We then derive concrete conditions for grasp synthesis and conduct experimental verification of our proposed method with an industrial manipulator.

/pdf/caging-based-grasping-of-deformable-objects-for-geometry-20seeivdm8.pdf

Caging-based grasping of deformable objects for geometry-based robotic manipulation

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Caging-based grasping of deformable objects for geometry-based robotic manipulation