A bipedal walking robot that can fly, slackline, and skateboard

An agile monopedal hopping quadcopter with synergistic hybrid locomotion

Nature abounds with examples of superior mobility through the fusion of aerial and ground movement. Drawing inspiration from such multimodal locomotion, we introduce a high-performance hybrid hopping and flying robot. The proposed robot seamlessly integrates a nano quadcopter with a passive telescopic leg, overcoming limitations of previous jumping mechanisms that rely on stance phase leg actuation. Based on the identified dynamics, a thrust-based control method and detachable active aerodynamic surfaces were devised for the robot to perform continuous jumps with and without position feedback. This unique design and actuation strategy enable tuning of jump height and reduced stance phase duration, leading to agile hopping locomotion. The robot recorded an average vertical hopping speed of 2.38 meters per second at a jump height of 1.63 meters. By harnessing multimodal locomotion, the robot is capable of intermittent midflight jumps that result in substantial instantaneous accelerations and rapid changes in flight direction, offering enhanced agility and versatility in complex environments. The passive leg design holds potential for direct integration with conventional rotorcraft, unlocking seamless hybrid hopping and flying locomotion.

Opto-fluidically multiplexed assembly and micro-robotics

Techniques for high-definition micromanipulations, such as optical tweezers, hold substantial interest across a wide range of disciplines. However, their applicability remains constrained by material properties and laser exposure. And while microfluidic manipulations have been suggested as an alternative, their inherent capabilities are limited and further hindered by practical challenges of implementation and control. Here we show that the iterative application of laser-induced, localized flow fields can be used for the relative positioning of multiple micro-particles, irrespectively of their material properties. Compared to the standing theoretical proposal, our method keeps particles mobile, and we show that their precision manipulation is non-linearly accelerated via the multiplexing of temperature stimuli below the heat diffusion limit. The resulting flow fields are topologically rich and mathematically predictable. They represent unprecedented microfluidic control capabilities that are illustrated by the actuation of humanoid micro-robots with up to 30 degrees of freedom, whose motions are sufficiently well-defined to reliably communicate personal characteristics such as gender, happiness and nervousness. Our results constitute high-definition micro-fluidic manipulations with transformative potential for assembly, micro-manufacturing, the life sciences, robotics and opto-hydraulically actuated micro-factories.

Multimodal Locomotion in a Soft Robot Through Hierarchical Actuation

Soft and continuum robots present the opportunity for extremely large ranges of motion, which can enable dexterous, adaptive, and multimodal locomotion behaviors. However, as the number of degrees of freedom (DOF) of a robot increases, the number of actuators should also increase to achieve the full actuation potential. This presents a dilemma in mobile soft robot design: physical space and power requirements restrict the number and type of actuators available and may ultimately limit the movement capabilities of soft robots with high-DOF appendages. Restrictions on actuation of continuum appendages ultimately may limit the various movement capabilities of soft robots. In this work, we demonstrate multimodal behaviors in an underwater robot called "Hexapus." A hierarchical actuation design for multiappendage soft robots is presented in which a single high-power motor actuates all appendages for locomotion, while smaller low-power motors augment the shape of each appendage. The flexible appendages are designed to be capable of hyperextension for thrust, and flexion for grasping with a peak pullout force of 32 N. For propulsion, we incorporate an elastic membrane connected across the base of each tentacle, which is stretched slowly by the high-power motor and released rapidly through a slip-gear mechanism. Through this actuation arrangement, Hexapus is capable of underwater locomotion with low cost of transport (COT = 1.44 at 16.5 mm/s) while swimming and a variety of multimodal locomotion behaviors, including swimming, turning, grasping, and crawling, which we demonstrate in experiment.

Vision-controlled jetting for composite systems and robots

Recreating complex structures and functions of natural organisms in a synthetic form is a long-standing goal for humanity1. The aim is to create actuated systems with high spatial resolutions and complex material arrangements that range from elastic to rigid. Traditional manufacturing processes struggle to fabricate such complex systems2. It remains an open challenge to fabricate functional systems automatically and quickly with a wide range of elastic properties, resolutions, and integrated actuation and sensing channels2,3. We propose an inkjet deposition process called vision-controlled jetting that can create complex systems and robots. Hereby, a scanning system captures the three-dimensional print geometry and enables a digital feedback loop, which eliminates the need for mechanical planarizers. This contactless process allows us to use continuously curing chemistries and, therefore, print a broader range of material families and elastic moduli. The advances in material properties are characterized by standardized tests comparing our printed materials to the state-of-the-art. We directly fabricated a wide range of complex high-resolution composite systems and robots: tendon-driven hands, pneumatically actuated walking manipulators, pumps that mimic a heart and metamaterial structures. Our approach provides an automated, scalable, high-throughput process to manufacture high-resolution, functional multimaterial systems.

Multi-Modal Mobility Morphobot (M4) with appendage repurposing for locomotion plasticity enhancement

Robot designs can take many inspirations from nature, where there are many examples of highly resilient and fault-tolerant locomotion strategies to navigate complex terrains by recruiting multi-functional appendages. For example, birds such as Chukars and Hoatzins can repurpose wings for quadrupedal walking and wing-assisted incline running. These animals showcase impressive dexterity in employing the same appendages in different ways and generating multiple modes of locomotion, resulting in highly plastic locomotion traits which enable them to interact and navigate various environments and expand their habitat range. The robotic biomimicry of animals' appendage repurposing can yield mobile robots with unparalleled capabilities. Taking inspiration from animals, we have designed a robot capable of negotiating unstructured, multi-substrate environments, including land and air, by employing its components in different ways as wheels, thrusters, and legs. This robot is called the Multi-Modal Mobility Morphobot, or M4 in short. M4 can employ its multi-functional components composed of several actuator types to (1) fly, (2) roll, (3) crawl, (4) crouch, (5) balance, (6) tumble, (7) scout, and (8) loco-manipulate. M4 can traverse steep slopes of up to 45 deg. and rough terrains with large obstacles when in balancing mode. M4 possesses onboard computers and sensors and can autonomously employ its modes to negotiate an unstructured environment. We present the design of M4 and several experiments showcasing its multi-modal capabilities.

An Aerial-Wall Robotic Insect That Can Land, Climb, and Take Off from Vertical Surfaces

Insects that can perform flapping-wing flight, climb on a wall, and switch smoothly between the 2 locomotion regimes provide us with excellent biomimetic models. However, very few biomimetic robots can perform complex locomotion tasks that combine the 2 abilities of climbing and flying. Here, we describe an aerial-wall amphibious robot that is self-contained for flying and climbing, and that can seamlessly move between the air and wall. It adopts a flapping/rotor hybrid power layout, which realizes not only efficient and controllable flight in the air but also attachment to, and climbing on, the vertical wall through a synergistic combination of the aerodynamic negative pressure adsorption of the rotor power and a climbing mechanism with bionic adhesion performance. On the basis of the attachment mechanism of insect foot pads, the prepared biomimetic adhesive materials of the robot can be applied to various types of wall surfaces to achieve stable climbing. The longitudinal axis layout design of the rotor dynamics and control strategy realize a unique cross-domain movement during the flying-climbing transition, which has important implications in understanding the takeoff and landing of insects. Moreover, it enables the robot to cross the air-wall boundary in 0.4 s (landing), and cross the wall-air boundary in 0.7 s (taking off). The aerial-wall amphibious robot expands the working space of traditional flying and climbing robots, which can pave the way for future robots that can perform autonomous visual monitoring, human search and rescue, and tracking tasks in complex air-wall environments.

A Multimodal, Reconfigurable Workspace Soft Gripper for Advanced Grasping Tasks

A new generation of soft functional materials and actuator designs has ushered the development of highly advanced soft grippers as adaptive alternatives to traditional rigid end-effectors for grasping and manipulation applications. While being advantageous over their rigid counterparts, soft gripper capabilities such as contact effort are mostly a consequence of the gripper workspace, which in turn is largely constrained by the gripper design. Moreover, soft grippers designed for highly specific grasping tasks such as scooping grains or wide payloads are usually limited in grasping other payload types or in their manipulation versatility. This article describes a reconfigurable workspace soft (RWS) gripper that exploits compliant structures and pneumatic actuators to reconfigure its workspace to suit a wide range of grasping tasks. To achieve desired kinematics, finite element analysis (FEA) studies are conducted to dictate actuator design and materials used. Various grasping modes and their reconfiguration of the gripper workspace are presented and characterized, including the gripper's capability to reliably scoop granular items with radii as small as 1.5 mm, precisely pick items as thin as 300 μm from flat surfaces, as well as grasp large convex, nonconvex, and deformable items as heavy as 1.4 kg. The RWS gripper can modify and increase its grasping workspace volume by 397%, enabling the widest range of grasping capabilities to date achieved by a single soft gripper.

Multi-environment robotic transitions through adaptive morphogenesis

The current proliferation of mobile robots spans ecological monitoring, warehouse management and extreme environment exploration, to an individual consumer's home^1-4. This expanding frontier of applications requires robots to transit multiple environments, a substantial challenge that traditional robot design strategies have not effectively addressed^5,6. For example, biomimetic design-copying an animal's morphology, propulsion mechanism and gait-constitutes one approach, but it loses the benefits of engineered materials and mechanisms that can be exploited to surpass animal performance^7,8. Other approaches add a unique propulsive mechanism for each environment to the same robot body, which can result in energy-inefficient designs^9-11. Overall, predominant robot design strategies favour immutable structures and behaviours, resulting in systems incapable of specializing across environments^12,13. Here, to achieve specialized multi-environment locomotion through terrestrial, aquatic and the in-between transition zones, we implemented 'adaptive morphogenesis', a design strategy in which adaptive robot morphology and behaviours are realized through unified structural and actuation systems. Taking inspiration from terrestrial and aquatic turtles, we built a robot that fuses traditional rigid components and soft materials to radically augment the shape of its limbs and shift its gaits for multi-environment locomotion. The interplay of gait, limb shape and the environmental medium revealed vital parameters that govern the robot's cost of transport. The results attest that adaptive morphogenesis is a powerful method to enhance the efficiency of mobile robots encountering unstructured, changing environments.

CLOVER Robot: A Minimally Actuated Jumping Robotic Platform

Robots have been critical instruments to exploration of extreme environments by providing access to environments beyond human limitations. Jumping robot concepts are attractive solutions to negotiate complex and cluttered terrain. However, among the engineering challenges that need to be addressed to enable sustained operation of jumping robot concepts in extreme environments, the reduction of mechanical failure modes is one of the most fundamental. This study sets out to develop a jumping robot design, with a focus on a minimal actuation to support reduced mechanism maintenance and thus limit the number of mechanical failure modes. We present the synthesis of a Sarrus-style linkage to constrain the system to a single translational degree of freedom thus removing the need for synchronising gears, which exhibit high failure rates in dusty environments. We have restricted the present research to vertical solid jumps to assess the performance of the fundamental main-drive linkage. A laboratory demonstrator assists the transfer of theoretical concepts and approaches to practical implementation. The laboratory demonstrator performs jumps with 63% potential-to-kinetic energy conversion efficiency, with a theoretical maximum of 73%. Satisfactory operation opens up design optimisation and directional jump capability towards the development of a jumping robotic platform for extreme environments exploration.

Recent Advances in Bipedal Walking Robots: Review of Gait, Drive, Sensors and Control Systems

Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the bipedal movement is unstable. The influences of passive or active gait on energy demand are also discussed. Most studies are explored based on the zero moment. Furthermore, a review of the knowledge on the specific locomotor characteristics of birds, whose kinematics are derived from dinosaurs and provide them with both walking and running abilities, is presented. Secondly, many types of bipedal robot solutions are reviewed, which include nature-inspired robots (human-like and birdlike robots) and innovative robots using new heuristic, synthetic ideas for locomotion. Totally 45 robotic solutions are gathered by thebibliographic search method. Atlas was mentioned as one of the most perfect human-like robots, while the birdlike robot cases were Cassie and Digit. Innovative robots are presented, such asslider robot without knees, robots with rotating feet (3 and 4 degrees of freedom), and the hybrid robot Leo, which can walk on surfaces and fly. In particular, the paper describes in detail the robots' propulsion systems (electric, hydraulic), the structure of the lower limb (serial, parallel, mixed mechanisms), the types and structures of control and sensor systems, and the energy efficiency of the robots. Terrain roughness recognition systems using different sensor systems based on light detection and ranging or multiple cameras are introduced. A comparison of performance, control and sensor systems, drive systems, and achievements of known human-like and birdlike robots is provided. Thirdly, for the first time, the review comments on the future of bipedal robots in relation to the concepts of conventional (natural bipedal) and synthetic unconventional gait. We critically assess and compare prospective directions for further research that involve the development of navigation systems, artificial intelligence, collaboration with humans, areas for the development of bipedal robot applications in everyday life, therapy, and industry.

Neural-Fly enables rapid learning for agile flight in strong winds

Executing safe and precise flight maneuvers in dynamic high-speed winds is important for the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the relationship between various wind conditions and its effect on aircraft maneuverability is not well understood, it is challenging to design effective robot controllers using traditional control design methods. We present Neural-Fly, a learning-based approach that allows rapid online adaptation by incorporating pretrained representations through deep learning. Neural-Fly builds on two key observations that aerodynamics in different wind conditions share a common representation and that the wind-specific part lies in a low-dimensional space. To that end, Neural-Fly uses a proposed learning algorithm, domain adversarially invariant meta-learning (DAIML), to learn the shared representation, only using 12 minutes of flight data. With the learned representation as a basis, Neural-Fly then uses a composite adaptation law to update a set of linear coefficients for mixing the basis elements. When evaluated under challenging wind conditions generated with the Caltech Real Weather Wind Tunnel, with wind speeds up to 43.6 kilometers/hour (12.1 meters/second), Neural-Fly achieves precise flight control with substantially smaller tracking error than stateof-the-art nonlinear and adaptive controllers. In addition to strong empirical performance, the exponential stability of Neural-Fly results in robustness guarantees. Last, our control design extrapolates to unseen wind conditions, is shown to be effective for outdoor flights with only onboard sensors, and can transfer across drones with minimal performance degradation.

A Vision-Based Approach for Autonomous Motion in Cluttered Environments

In order to complete various tasks automatically, robots need to have onboard sensors to gain the ability to move autonomously in complex environments. Here, we propose a combined strategy to achieve the real-time, safe, and smooth autonomous motion of robots in complex environments. The strategy consists of the building of an occupancy grid map of the environment in real time via the binocular system, followed by planning a smooth and safe path based on our proposed new motion-planning algorithm. The binocular system, which is small in size and lightweight, can provide reliable robot position, attitude, and obstacle information, enabling the establishment of an occupancy grid map in real time. Our proposed new algorithm can generate a high-quality path by using the gradient information of the ESDF (Euclidean Signed Distance Functions) value to adjust the waypoints. Compared with the reported motion-planning algorithm, our proposed algorithm possesses two advantages: (i) ensuring the security of the entire path, rather than that of the waypoints; and (ii) presenting a fast calculation method for the ESDF value of the path points, one which avoids the time-consuming construction of the ESDF map of the environment. Experimental and simulation results demonstrate that the proposed method can realize the safe and smooth autonomous motion of the robot in a complex environment in real time. Therefore, our proposed approach shows great potential in the application of robotic autonomous motion tasks.

Mechanism Design of a Transformable Crawling Robot and Feasibility Analysis for the Unstructured Environment

The better application of crawl robots depends on their ability to adapt to unstructured environments with significant variations in their structural shape and size. This paper presents the design and analysis of a novel robot with different locomotion configurations to move through varying environments. The leg of the robot, inspired by insects, was designed as a multi-link structure, including the Hoekens linkage and multiple parallel four-link mechanisms. The end trajectory was a symmetrical closed curve composed of an approximate straight line and a shell curve with a downward opening. The special trajectory allowed the robot to share drives and components to achieve structural deformation and locomotion. The structural characteristics of the crawl robot on the inner and outer arcs were obtained based on the working space. The constraint relationship between the structure size, the radius of the arc, and the coefficient of static friction with which the robot could crawl on the arc were established. The feasible support posture and support position of the robot under different arc radii were obtained. The simulation tested the locomotion of the robot on the plane, arc, and restricted space. The robot can be used for detection, search, and rescue missions in unstructured environments.

A professional slackliner robot

[Figure: see text].