SCALER: Versatile Multi-Limbed Robot for Free-Climbing in Extreme Terrains

This paper presents SCALER, a versatile free-climbing multi-limbed robot that is designed to achieve tightly coupled simultaneous locomotion and dexterous grasping. Although existing quadruped-limbed robots have shown impressive dexterous skills such as object manipulation, it is essential to balance power-intensive locomotion and dexterous grasping capabilities. We design a torso linkage and a parallel-serial limb to meet such conflicting skills that pose unique challenges in the hardware designs. SCALER employs underactuated two-fingered GOAT grippers that can mechanically adapt and offer 7 modes of grasping, enabling SCALER to traverse extreme terrains with multi-modal grasping strategies. We study the whole-body approach, where SCALER uses its body and limbs to generate additional forces for stable grasping with environments, further enhancing versatility. Furthermore, we improve the GOAT gripper actuation speed to realize more dynamic climbing in a closed-loop control fashion. With these proposed technologies, SCALER can traverse vertical, overhang, upside-down, slippery terrains, and bouldering walls with non-convex-shaped climbing holds under the Earth's gravity

Motion Planning for a Climbing Robot with Stochastic Grasps

Motion planning for a multi-limbed climbing robot must consider the robot's posture, joint torques, and how it uses contact forces to interact with its environment. This paper focuses on motion planning for a robot that uses nontraditional locomotion to explore unpredictable environments such as martian caves. Our robotic concept, ReachBot, uses extendable and retractable booms as limbs to achieve a large reachable workspace while climbing. Each extendable boom is capped by a microspine gripper designed for grasping rocky surfaces. ReachBot leverages its large workspace to navigate around obstacles, over crevasses, and through challenging terrain. Our planning approach must be versatile to accommodate variable terrain features and robust to mitigate risks from the stochastic nature of grasping with spines. In this paper, we introduce a graph traversal algorithm to select a discrete sequence of grasps based on available terrain features suitable for grasping. This discrete plan is complemented by a decoupled motion planner that considers the alternating phases of body movement and end-effector movement, using a combination of sampling-based planning and sequential convex programming to optimize individual phases. We use our motion planner to plan a trajectory across a simulated 2D cave environment with at least 95% probability of success and demonstrate improved robustness over a baseline trajectory. Finally, we verify our motion planning algorithm through experimentation on a 2D planar prototype.Comment: 7 pages, 7 figure

Microspine Gripping Mechanism for Asteroid Capture

This paper details the development and early testing of a compliant suspension for a microspine gripper device for asteroid capture or micro-gravity percussive drilling. The microspine gripper architecture is reviewed, and a proposed microspine suspension design is presented and discussed. Prototyping methods are discussed, as well as testing methods and results. A path forward is identified from the results of the testing completed thus far. Key findings include: the microspine concept has been established as a valid architecture and the compliant suspension exhibits the desired stiffness characteristics for good gripping behavior. These developments will aid in developing the capability to grasp irregularly shaped boulders in micro-gravity

A Skeleton-based Approach For Rock Crack Detection Towards A Climbing Robot Application

Conventional wheeled robots are unable to traverse scientifically interesting, but dangerous, cave environments. Multi-limbed climbing robot designs, such as ReachBot, are able to grasp irregular surface features and execute climbing motions to overcome obstacles, given suitable grasp locations. To support grasp site identification, we present a method for detecting rock cracks and edges, the SKeleton Intersection Loss (SKIL). SKIL is a loss designed for thin object segmentation that leverages the skeleton of the label. A dataset of rock face images was collected, manually annotated, and augmented with generated data. A new group of metrics, LineAcc, has been proposed for thin object segmentation such that the impact of the object width on the score is minimized. In addition, the metric is less sensitive to translation which can often lead to a score of zero when computing classical metrics such as Dice on thin objects. Our fine-tuned models outperform previous methods on similar thin object segmentation tasks such as blood vessel segmentation and show promise for integration onto a robotic system

Objekt-Manipulation und Steuerung der Greifkraft durch Verwendung von Taktilen Sensoren

This dissertation describes a new type of tactile sensor and an improved version of the dynamic tactile sensing approach that can provide a regularly updated and accurate estimate of minimum applied forces for use in the control of gripper manipulation. The pre-slip sensing algorithm is proposed and implemented into two-finger robot gripper. An algorithm that can discriminate between types of contact surface and recognize objects at the contact stage is also proposed. A technique for recognizing objects using tactile sensor arrays, and a method based on the quadric surface parameter for classifying grasped objects is described. Tactile arrays can recognize surface types on contact, making it possible for a tactile system to recognize translation, rotation, and scaling of an object independently.Diese Dissertation beschreibt eine neue Art von taktilen Sensoren und einen verbesserten Ansatz zur dynamischen Erfassung von taktilen daten, der in regelmäßigen Zeitabständen eine genaue Bewertung der minimalen Greifkraft liefert, die zur Steuerung des Greifers nötig ist. Ein Berechnungsverfahren zur Voraussage des Schlupfs, das in einen Zwei-Finger-Greifarm eines Roboters eingebaut wurde, wird vorgestellt. Auch ein Algorithmus zur Unterscheidung von verschiedenen Oberflächenarten und zur Erkennung von Objektformen bei der Berührung wird vorgestellt. Ein Verfahren zur Objekterkennung mit Hilfe einer Matrix aus taktilen Sensoren und eine Methode zur Klassifikation ergriffener Objekte, basierend auf den Daten einer rechteckigen Oberfläche, werden beschrieben. Mit Hilfe dieser Matrix können unter schiedliche Arten von Oberflächen bei Berührung erkannt werden, was es für das Tastsystem möglich macht, Verschiebung, Drehung und Größe eines Objektes unabhängig voneinander zu erkennen

Towards understanding of climbing, tip-over prevention and self-righting behaviors in Hexapoda

Die vorliegende Dissertation mit dem Titel “Towards understanding of climbing, tip-over prevention and self-righting behaviors in Hexapoda” untersucht in drei Studien exemplarisch, wie (i) Wüstenameisen ihre Beine einsetzen um An- und Abstiege zu überwinden, wie (ii) Wüsten- und Waldameisen ein Umkippen an steilen Anstiegen vermeiden, und wie sich (iii) Madagaskar-Fauchschaben, Amerikanische Großschaben und Blaberus discoidalis Audinet-Servill, 1839 aus Rückenlagen drehen und aufrichten. Neuartige biomechanischen Beschreibungen umfassen unter anderem: Impuls- und Kraftwirkungen einzelner Ameisenbeine auf den Untergrund beim Bergauf- und Bergabklettern, Kippmomente bei kletternden Ameisen, Energiegebirge-Modelle (energy landscapes) zur Quantifizierung der Körperform für die funktionelle Beschreibung des Umdrehens aus der Rückenlage

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility