Inchworms use their morphology and evolved behaviors to crawl and climb various complex surfaces. This has inspired the development of different robots that can demonstrate similar capabilities for various applications such as the inspection of a complex environment. One of the key challenges in designing these robots is to enable them to be practically deployable with a compact design for providing continuous adaptability to a complex terrain such as an outer-pipe surface. Taking this into consideration, we present a new design for an inchworm-inspired crawling robot (iCrawl). The 5 DOF robot relies on two legs; each with an electromagnetic foot, in order to crawl on the metal pipe surfaces. The robot uses a passive foot-cap underneath an electromagnetic foot, enabling it to be a versatile pipe-crawler. The foot-cap design is an abstraction of the leg posture in an inchworm adapting to a round surface. The proposed foot-caps give the robot adaptability and stability for crawling on metal pipes of various curvatures. A state-machine based controller was developed to produce the required motor signals for the two inchworm-inspired crawling gaits: i) the step gait, and ii) the sliding gait. Both gaits were tested on the robot, eventually leading to it effectively crawling on the pipes and flat surfaces, climbing a metal wall and a pipe, and succeeding in obstacle avoidance during crawling. Experimental results also show that the robot has the ability to crawl on the metal pipes of various curvatures using the foot-caps and an appropriate gait. The robot can be used as a new robotic solution to assist close inspection outside the pipelines, thus minimizing downtime in the oil and gas industry.

Ensuring both feasibility and reliability when measuring forces and torques in legged robots is challenging. Different transducer technologies and structural designs can be used to develop force/torque sensors with multiple measurement axes, high accuracy, and durability. Among the said technologies, strain gauges are frequently used, due to their high accuracy and compatibility with various materials. However, strain gauges also cause design challenges, because of their requirement for typically large housing structures, heavy workload during installation, and susceptibility to error from thermal expansion and fluids. This typically results in a high production cost that is further multiplied with the number of measuring axes. As a consequence, the sensors become extremely expensive and unsuitable for legged robots and outdoor applications. We propose a new design for a three-axis force/torque sensor that is low-cost, compact, and hermetically sealed. It uses a single torsion full-bridge strain gauge in combination with on-board data processing. We demonstrate the advantages of the sensor design in terms of error reduction without using Wheatstone Bridges for all axes, and subsequently, the measuring accuracy in all angles. Furthermore, we demonstrate the three-axis force sensing capabilities of the sensor on a bio-inspired walking robot. Accordingly, our results demonstrate error reduction methods that (1) offer an alternative to conventional methods, and (2) have suitable accuracy for applications such as foot sensors in walking robots. We believe that the sensor's on-board data processing and mass production compatibility can make force/torque sensing more accessible, leading to novel robotic applications in the future.

Morphology is a defining trait of any walking entity, animal or robot, and is crucial in obtaining movement versatility, dexterity and durability. Collaborations between biologist and engineers create opportunities for implementing bio-inspired morphologies in walking robots. However, there is little guidance for such interdisciplinary collaborations and what tools to use. We propose a development framework for transferring animal morphologies to robots and substantiate it with a replication of the ability of the dung beetle species Scarabaeus galenus to use the same morphology for both locomotion and object manipulation. As such, we demonstrate the advantages of a bio-inspired dung beetle-like robot, ALPHA, and how its morphology outperforms a conventional hexapod by increasing the (1) step length by 50.0%, (2) forward and upward reach by 95.5%, and by lowering the (3) overall motor acceleration by 7.9%, and (4) step frequency by 21.1% at the same walking speed. Thereby, the bio-inspired robot has longer and fewer steps that lower fatigue-inducing impulses, a greater variety of step patterns, and can potentially better utilise its workspace to overcome obstacles. Hence, we demonstrate how the framework can be used to develop legged robots with bio-inspired morphologies that embody greater movement versatility, dexterity and durability.

Dynamic compliant robotics is a fast growing field because of its ability to widen the scope of robotics. The reason for this is that compliant mechanisms may ensure safe/compliant interactions between a robot and an external element—for instance, a human operator. Active impedance control may widen the scope even further in relation to passive elements, but it requires high-bandwidth robust torque and active impedance control which induces high-noise issues even if high-end sensors are used. To address these issues, a complete controller design scheme, including Field-Oriented Control (FOC) of a Brushless Direct Current (BLDC) motor, is proposed. In this paper, controller designs for controlling the virtual impedance, motor torque and field are proposed which enables high-bandwidth robust control. Additionally, a novel speed and angle observer is proposed that aims to reduce noise arising in the angle sensor (typically a 12-bit magnetic encoder) and a Kalman/Luenberger based torque observer is proposed that aims to reduce noise arising in the phase current sensors. Through experimental tests, the combination of the controller designs and observers facilitated a closed-loop torque bandwidth of $2.6$ $\mathrm{k}$ $\mathrm{Hz}$ and a noise reduction of $13.5$ dB (in relation to no observers), at a sample rate and Pulse Width Modulation (PWM) frequency of 25 $\mathrm{k}$ $\mathrm{Hz}$ . Additionally, experiments verified a precise and high performing controller scheme both during impacts and at a variety of different virtual compliance characteristics.

Dung beetles can effectively transport dung pallets of various sizes in any direction across uneven terrain. While this impressive ability can inspire new locomotion and object transportation solutions in multilegged (insect-like) robots, to date, most existing robots use their legs primarily to perform locomotion. Only a few robots can use their legs to achieve both locomotion and object transportation, although they are limited to specific object types/sizes (10%–65% of leg length) on flat terrain. Accordingly, we proposed a novel integrated neural control approach that, like dung beetles, pushes state-of-the-art insect-like robots beyond their current limits toward versatile locomotion and object transportation with different object types/sizes and terrains (flat and uneven). The control method is synthesized based on modular neural mechanisms, integrating central pattern generator (CPG)-based control, adaptive local leg control, descending modulation control, and object manipulation control. We also introduced an object transportation strategy combining walking and periodic hind leg lifting for soft object transportation. We validated our method on a dung beetle-like robot. Our results show that the robot can perform versatile locomotion and use its legs to transport hard and soft objects of various sizes (60%–70% of leg length) and weights (approximately 3%–115% of robot weight) on flat and uneven terrains. The study also suggests possible neural control mechanisms underlying the dung beetle Scarabaeus galenus’ versatile locomotion and small dung pallet transportation.