In this paper we explore kinematics ranging from anguilliform to thunniform achieved in a self-sensing multi-degree-of-freedom soft robotic fish and analyze the effect of them on the swimming. First, we examine the characteristics of the bending actuators of the robotic fish. Then, we express the kinematics of the fish as a propagating wave parameterized by three bending amplitudes and a wavelength, which are determined by the flow rates and phase shift of the pumps. We capture various motion patterns generated by different actuator inputs and directly measure the thrust generated by each pattern. We observe that the robotic swimmer can reproduce two different modes of propulsion, that are embodied by two distinct morphological patterns in nature: anguilliform and thunniform. When neither of modes are activated, propulsion is zero or even negative. Finally, we estimate the stationary swimming speed by towing the undulating fish, which satisfies the slip condition (with the speed of the body wave matching the swimming velocity). The analysis of a wide range of kinematic patterns in this study, including two extreme cases of anguilliform and thunniform modes, will provide insights for comprehensive understanding the mechanics of efficient swimming.

Existing robots designed for locomotion in granular media typically excel at a single purpose—either surface travel or subsurface digging—while lacking the ability to perform both within the same platform. In contrast, nature offers various examples of burrowing organisms that exhibit multi-functional digging behaviors by separating their body into two essential parts: a digger for substrate intrusion and rest of the body as anchor for stabilization and controlling digger orientation. Inspired by these biological strategies, we present an extension to an existing Screw Propelled Vehicle (SPV) that incorporates an adjustable body anchor to reduce drag and enable orientation control. This integration allows the robot to transition between horizontal crawling and vertical digging. We also investigate the effect of local fluidization (LF), a bio-inspired technique that temporarily reduces the resistive forces in granular media. Experimental results show that integrating LF improves surface propulsion performance in terms of speed and depth with increment of over 5x compared to the baseline configuration. These findings support the hypothesis that bio-inspired design principles—specifically body–anchor separation and local fluidization—significantly enhance both the functionality and efficiency of granular locomotion robots, providing a pathway toward more versatile, autonomous, and high-performance subsurface exploration.

Capturing large objects of unknown shape and orientation remains a challenge for most robotic grippers. We present a highly under-actuated gripper well suited for this task. Prior work shows two primary limitations to these grippers: the grip force of each link tends to decrease as the number of links increases, and the stability of an under-actuated linkage depends on the configuration of the links so grippers with many links are unlikely to be stable for arbitrary surfaces. We address these concerns by implementing two complementary methods of stabilization: using high-friction materials and scaling forces into the surface. We show that gecko-inspired adhesives provide an adhesion-controlled friction that can stabilize the gripper and improve grasp performance without the need of large normal forces. The under-actuated linkages also conform around arbitrary shapes and provide capability beyond prior adhesion-based grippers. With these high-friction interfaces, we show highly under-actuated linkages successfully grasp in many configurations without strict stability. The gripper is capable of holding over 30 N and consists of two tendon driven linkages that are each 65 cm long. This type of gripper is well suited for tasks without a predefined target geometry or orientation such as satellite servicing.

This paper presents an end-to-end approach to automate the design and fabrication process for self-folding origami structures. Self-folding origami structures are robotic sheets composed of rigid tiles and joint actuators. When they are exposed to heat, each joint folds into a preprogrammed angle. Those folding motions transform themselves into a structure, which can be used as body of 3-D origami robots, including walkers, analog circuits, rotational actuators, and microcell grippers. Given a 3-D model, the design algorithm automatically generates a layout printing design of the sheet form of the structure. The geometric information, such as the fold angles and the folding sequences, is embedded in the sheet design. When the sheet is printed and baked in an oven, the sheet self-folds into the given 3-D model. We discuss, first, the design algorithm generating multiple-step self-folding sheet designs, second, verification of the algorithm running in O(n2) time, where n is the number of the vertices, third, implementation of the algorithm, and finally, experimental results, several self-folded 3-D structures with up to 55 faces and two sequential folding steps.

Soft robots have recently demonstrated impressive abilities to adapt to objects and their environment with limited sensing and actuation. However, mobile soft robots are typically fabricated using laborious molding processes that result in limited actuated degrees of freedom and hence limited locomotion capabilities. In this paper, we present a 3D printed robot with bellowed soft legs capable of rotation about two axes. This allows our robot to navigate rough terrain that previously posed a significant challenge to soft robots. We present models and FEM simulations for the soft leg modules and predict the robot locomotion capabilities. We use finite element analysis to simulate the actuation characteristics of these modules. We then compared the analytical and computational results to experimental results with a tethered prototype. The experimental soft robot is capable of lifting its legs 5.3 cm off the ground and is able to walk at speeds up to 20 mm/s (0.13 bl/s). This work represents a practical approach to the design and fabrication of functional mobile soft robots.

Fluidically actuated soft robots show a great promise for operation in sensitive and unknown environments due to their intrinsic compliance. However, most previous designs use either flow control systems that are noisy, inefficient, sensitive to leaks, and cannot achieve differential pressure (i.e. can only apply either positive or negative pressures with respect to atmospheric), or closed volume control systems that are not adaptable and prohibitively expensive. In this paper, we present a modular, low cost volume control system for differential pressure control of soft actuators. We use this system to actuate three-chamber 3D printed soft robotic modules. For this design, we find a 54% increase in achievable blocked force, and a significant increase in actuator workspace when using differential pressure actuation as compared to the use of only pressure or vacuum. The increased workspace allowed the robot to achieve complex tasks such as writing on a screen with a laser pointer or manipulating fragile objects. Furthermore, we demonstrate a self-healing capability of the combined system by using vacuum to actuate ruptured modules which were no longer responsive to positive pressure.

Robots are becoming increasingly prevalent in our society in forms where they are assisting or interacting with humans in a variety of environments, and thus they must have the ability to sense and detect objects by touch. An ongoing challenge for soft robots has been incorporating flexible sensors that can recognize complex motions and close the loop for tactile sensing. We present sensor skins that enable haptic object visualization when integrated on a soft robotic gripper that can twist an object. First, we investigate how the design of the actuator modules impact bend angle and motion. Each soft finger is molded using a silicone elastomer, and consists of three pneumatic chambers which can be inflated independently to achieve a range of complex motions. Three fingers are combined to form a soft robotic gripper. Then, we manufacture and attach modular, flexible sensory skins on each finger to measure deformation and contact. These sensor measurements are used in conjunction with an analytical model to construct 2D and 3D tactile object models. Our results are a step towards soft robot grippers capable of a complex range of motions and proprioception, which will help future robots better understand the environments with which they interact, and has the potential to increase physical safety in human-robot interaction. Please see the accompanying video for additional details.

Large robotic collectives provide advantages such as resilience to mechanical failure of single agents and increased capabilities for search and coverage based applications. However, a lack of rapid and free-form manufacturing processes remains a barrier to high-volume fabrication of mechanically heterogeneous robotic swarms. Self-folding laser-machined structures have the potential to enable heterogeneous robotic swarms. As an initial step to realizing a functional robotic collective, we focus on the design and characterization of the locomotion of an individual laminate manufactured robot. We look to a vibration-based locomotion technique that uses flexible structures or bristles to enhance the effects of vibration, allowing for fast locomotion (i.e. a “bristle-bot”). However, previous bristle-bot implementations have not allowed for controllable steering behaviors with high locomotion speeds. We describe the extension of existing two dimensional bristle-bot models to a three dimensional model that explores parameters that govern linear and angular velocity. We implement an autonomous laminate-manufactured bristle-bot inspired robot capable of linear velocities of up to 23 cm/s and turning rates of 2 rad/s. Moving towards automated manufacturing, we also demonstrate a self-folding bristle-bot structure that uses a linear compression laminate to achieve a uniform leg fold angle.

The agility and ease of control make a quadrotor aircraft an attractive platform for studying swarm behavior, modeling, and control. The energetics of sustained flight for small aircraft, however, limit typical applications to only a few minutes. Adding payloads - and the mechanisms used to manipulate them - reduces this flight time even further. In this paper we present the flying monkey, a novel robot platform having three main capabilities: walking, grasping, and flight. This new robotic platform merges one of the world's smallest quadrotor aircraft with a lightweight, single-degree-of-freedom walking mechanism and an SMA-actuated gripper to enable all three functions in a 30 g package. The main goal and key contribution of this paper is to design and prototype the flying monkey that has increased mission life and capabilities through the combination of the functionalities of legged and aerial robots.

Self-folding provides an efficient way of creating complex 3D geometries from 2D composites. However, the precision of self-folding structures is often limited by the use of open-loop folding mechanisms. In this paper we demonstrate feedback-controlled self-folding using a shape memory polymer and optical sensors to accurately control folding angles. We present a method of quickly and inexpensively fabricating large collectives of self-folding autonomous robots that can be transported in flat configurations prior to autonomous deployment at target destinations. To demonstrate this, we build a collective of robots that is manufactured in one continuous laminar composite. Individual robots in the collective detach from one other, self-fold into pre-programmed configurations and navigate by phototaxis. This method could be applied to a broad range of applications where logistics necessitate compact transport and where external manipulation is difficult or expensive, such as in space applications or delivering search-and-rescue robots in cluttered environments.

This paper presents an end-to-end approach for creating 3D shapes by self-folding planar sheets activated by uniform heating. These shapes can be used as the mechanical bodies of robots. The input to this process is a 3D geometry (e.g. an OBJ file). The output is a physical object with the specified geometry. We describe an algorithm pipeline that (1) identifies the overall geometry of the input, (2) computes a crease pattern that causes the sheet to self-fold into the desired 3D geometry when activated by uniform heating, (3) automatically generates the design of a 2D sheet with the desired pattern and (4) automatically generates the design files required to fabricate the 2D structure. We demonstrate these algorithms by applying them to complex 3D shapes. We demonstrate the fabrication of a self-folding object with over 50 faces from automatically generated design files.

We present a method for setting the pressure of multiple chambers using a single pressure source when they are interconnected via band-pass valves. These valves can be constructed from simple passive devices that behave like leaky check valves. We present the theory of operation and design parameters for individual valves, give a control strategy for serial connections of pressure chambers, and demonstrate the approach by building prototype valves and using them to control serially connected soft-robotic actuators from a single pressure source.

Self-assembled structures and machines can be made using origami-inspired manufacturing methods. In particular, self-folding of two-dimensional materials using shape memory polymers and embedded electrical circuits has been utilized to build robots and structures in an inexpensive and rapid manner. In order to build increasingly complex and functional self-folding machines, however, methods for interaction with the environment are necessary. This paper presents and characterizes three types of self-folding sensors: a mechanical switch, a capacitive contact sensor, and a velocity sensor. We utilize specialized fold patterns to create cyclic mechanical linkages as well as additional composite layers such as magnetic sheets to build these sensors. We demonstrate the integration of two of these sensors, the switch and the contact sensor, into a lamp that can self-fold and immediately begin responding to its surroundings.

Locomoting soft robots typically walk or crawl slowly relative to their rigid counterparts. In order to execute agile behaviors such as jumping, rapid actuation modes are required. Here we present an untethered soft-bodied robot that uses a combination of pneumatic and explosive actuators to execute directional jumping maneuvers. This robot can autonomously jump up to 0.6 meters laterally with an apex of up to 0.6 meters (7.5 times it's body height) and can achieve targeted jumping onto an object. The robot is able to execute these directed jumps while carrying the required fuel, pneumatics, control electronics, and battery. We also present a thermodynamic model for the combustion of butane used to power jumping, and calculate the theoretical maximum work output for the design. From experimental results, we find the mechanical efficiency of this prototype to be 0.8%.

Printing and folding are fast and inexpensive methods for prototyping complex machines. Self-assembly of the folding step would expand the possibilities of this method to include applications where external manipulation is costly, such as micro-assembly, mass production, and space applications. This paper presents a method for self-folding of printed robots from two-dimensional materials based on shape memory polymers actuated by joule heating using embedded circuits. This method was shown to be capable of sequential folding, angle-controlled folds, slot-and-tab assembly, and mountain and valley folds. An inchworm robot was designed to demonstrate the merits of this technique. Upon the application of sufficient current, the robot was able to fold into its functional form with fold angle deviations within six degrees. This printed robot demonstrated locomotion at a speed of two millimeters per second.

Nature regularly uses self-folding as an efficient approach to automated fabrication. In engineered systems, however, the use of self-folding has been primarily restricted to the assembly of small structures using exotic materials and/or complex infrastructures. In this paper we present three approaches to the self-folding of structures using low-cost, rapid-prototyped shape memory laminates. These structures require minimal deployment infrastructure, and are activated by light, heat, or electricity. We compare the fabrication of a fundamental structure (a cube) using each approach, and test ways to control fold angles in each case. Finally, for each self-folding approach we present a unique structure that the approach is particularly suited to fold, and discuss the advantages and disadvantages of each approach.

Self-reconfiguring modular robotic systems offer a potential route to achieving programmable matter, i.e. a substance the shape and properties of which can be tuned as required to achieve a variety of tasks. However, most modular robotic system designs rely on deterministic module motions which place significant power, control, and actuation requirements on the individual modules. This leads to relatively large modules and low target structure resolution. Here we experimentally demonstrate an alternative approach based on stochastic assembly, in which modules assemble into target structures in a fluidic tank. This system employs ambient fluid motion for module transportation. Assembly is directed by controlling the fluid flow through an active assembly substrate with an array of valves. Different valving programs are used with feedback from pressure sensors to achieve the completely automated hierarchical assembly of non-planar 3D structures.

One of the grand challenges of self-reconfiguring modular robotics is the assembly of a functional system from thousands of components. However, to date, only systems comprised of small numbers of modules have been demonstrated. One approach to scaling to large numbers of modules is to simplify module design by relieving the modules of the typical power, control, and actuation requirements necessary for locomotion. Assembly is accomplished by taking advantage of stochastic environmental motions to move the modules into place. Here we present an experimental system in which we assemble 3D target structures stochastically from simple, 15 mm-scaled components by manipulating the fluid flow in a 1.3 L tank. We also demonstrate fundamental assembly and repair operations experimentally, and discuss initial assembly statistics.

Modular robotic systems typically assemble using deterministic processes where modules are directly placed into their target position. By contrast, stochastic modular robots take advantage of ambient environmental energy for the transportation and delivery of robot components to target locations, thus offering potential scalability. The inability to precisely predict component availability and assembly rates is a key challenge for planning in such environments. Here, we describe a computationally efficient simulator to model a modular robotic system that assembles in a stochastic fluid environment. This simulator allows us to address the challenge of planning for stochastic assembly by testing a series of potential strategies. We first calibrate the simulator using both high-fidelity computational fluid-dynamics simulations and physical experiments. We then use this simulator to study the effects of various system parameters and assembly strategies on the speed and accuracy of assembly of topologically different target structures.