Gripper hardware design often involves a trade-off between distinct and sometimes opposing goals (e.g., high grasping force vs. gentleness). To address this trade-off within a single device, we present a multi-mode gripper with fingers that are scissor linkages, that can actively transform between three distinct modes by varying the number and locations of mechanical singularities. Each of these modes has properties that are suitable for specific needs. Mode 1 provides high grip strength, using a short lever arm and rigid structure. Mode 2 allows precise finger positioning and in-hand manipulation, using two independently controlled DOFs per finger. Mode 3 provides underactuated grasping that can passively adapt to delicate or irregularly shaped objects, with four DOFs per finger. The kinematic relationships, joint torques, and fingertip forces are derived analytically for each of the three modes. Gripper performance and the kinematic model are verified experimentally.

We consider cooperative manipulation by multiple robots assisting a leader, when information about the manipulation task, environment, and team of helpers is unavailable, and without the use of explicit communication. The shared object being manipulated serves as a physical channel for coordination, with robots sensing forces associated with its movement. Robots minimize force conflicts, which are unavoidable under these restrictions, by inferring an intended context: decomposing the object's motion into a task space of allowed motion and a null space in which perturbations are rejected. The leader can signal a change in context by applying a sustained strong force in an intended new direction. We present a controller, prove its stability, and demonstrate its utility through experiments with (a) an in-lab force-sensitive robot assisting a human operator and (b) a multi-robot collective in simulation.

Coordinated movement in animal groups (flocks, schools, herds, etc.) is a classic and well-studied form of collective behaviour. Most theoretical studies consider agents in unobstructed spaces; however, many animals move in often complicated environments and must navigate around and through obstacles. Here we consider simulated agents behaving according to typical flocking rules, with the addition of repulsion from obstacles, and study their collective behaviour in environments with concave obstacles (dead ends). We find that groups of such agents heading for a goal can spontaneously escape dead ends without wall-following or other specialized behaviours, in what we term ‘flocking escapes’. The mechanism arises when agents align with one another while heading away from the goal, forming a self-stable cluster that persists long enough to exit the obstacle and avoids becoming trapped again when turning back towards the goal. Solitary agents under the same conditions are never observed to escape. We show that alignment with neighbours reduces the effective turning speed of the group while letting individuals maintain high manoeuvrability when needed. The relative robustness of flocking escapes in our studies suggests that this emergent behaviour may be relevant for a variety of animal species.

Robots are increasingly being called on to operate in settings and on tasks originally designed for humans, or where humans are also expected to work. Accordingly, the hardware and tools to be packaged, operated, or maintained are typically designed for use by humans, not robots. Robot autonomy in such cases can be expedited by a "robot factors" approach to the design of hardware, analogous to ergonomics for humans, taking typical current robot capabilities into account during the design process. In this paper, we present two case studies of redesigning mission-critical hardware in space habitats to facilitate autonomous robot operation. In both cases, hardware that previously required dexterous bi-manual manipulation is redesigned such that the entire maintenance task can be completed by a single robotic arm with a standard parallel jaw gripper. We demonstrate successful autonomous replacement of modules in the two hardware systems, and characterize how orientation and compliance of a grasp helps compensate for positioning errors. Based on our findings, we identify several key design strategies that underpin the robot factors approach to designing robot-friendly hardware, including consolidating compound actions into simpler mechanisms, constraining required motions to a single axis, and introducing mechanical compliance to decrease the effects of pose uncertainties.

In this paper, we discuss the role of gripper compliance in successful grasping and manipulation of thin, flexible materials. We show, both conceptually and empirically, that each axis of compliance in a planar gripper provides unique benefits in this domain. Vertical compliance allows robust grasping of thin materials in the presence of large uncertainty in positioning. Lateral compliance increases opportunity to respond to unexpected snags by increasing the time window over which tensile forces are applied. Rotational compliance avoids damage to objects by decreasing the maximum tensile forces applied during snags. We explore these three benefits through empirical tests comparing a rigid gripper to a soft gripper, evaluating the level of vertical uncertainty each can handle for prehensile and non-prehensile manipulation, as well as the forces and displacements incurred during snags. The results show how a soft gripper's three-axis compliance provides a passive ability to prevent damage to delicate materials.

Soft robots offer a host of benefits over traditional rigid robots, including inherent compliance that lets them passively adapt to variable environments and operate safely around humans and fragile objects. However, that same compliance makes it hard to use model-based methods in planning tasks requiring high precision or complex actuation sequences. Reinforcement learning (RL) can potentially find effective control policies, but training RL using physical soft robots is often infeasible, and training using simulations has had a high barrier to adoption. To accelerate research in control and RL for soft robotic systems, we introduce SoMoGym (Soft Motion Gym), a software toolkit that facilitates training and evaluating controllers for continuum robots. SoMoGym provides a set of benchmark tasks in which soft robots interact with various objects and environments. It allows evaluation of performance on these tasks for controllers of interest, and enables the use of RL to generate new controllers. Custom environments and robots can likewise be added easily. We provide and evaluate baseline RL policies for each of the benchmark tasks. These results show that SoMoGym enables the use of RL for continuum robots, a class of robots not covered by existing benchmarks, giving them the capability to autonomously solve tasks that were previously unattainable.

An Earth-independent permanent extraterrestrial habitat system must function as intended under continuous disruptive conditions, and with significantly limited Earth support and extended uncrewed periods. Designing for the demands that extreme environments such as wild temperature fluctuations, galactic cosmic rays, destructive dust, meteoroid impacts (direct or indirect), vibrations, and solar particle events, will place on long-term deep space habitats represents one of the greatest challenges in this endeavor. This context necessitates that we establish the know-how and technologies to build habitat systems that are resilient. Resilience is not simply robustness or redundancy: it is a system property that accounts for both anticipated and unanticipated disruptions via the design choices and maintenance processes, and adapts to them in operation. We currently lack the frameworks and technologies needed to achieve a high level of resilience in a habitat system. The Resilient ExtraTerrestrial Habitats Institute (RETHi) has the mission of leveraging existing novel technologies to provide situational awareness and autonomy to enable the design of habitats that are able to adapt, absorb and rapidly recover from expected and unexpected disruptions. We are establishing both fully virtual and coupled physical-virtual simulation capabilities that will enable us to explore a wide range of potential deep space SmartHab configurations and operating modes.

Many species of termites build large, structurally complex mounds, and the mechanisms behind this coordinated construction have been a longstanding topic of investigation. Recent work has suggested that humidity may play a key role in the mound expansion of savannah-dwelling Macrotermes species: termites preferentially deposit soil on the mound surface at the boundary of the high-humidity region characteristic of the mound interior, implying a coordination mechanism through environmental feedback where addition of wet soil influences the humidity profile and vice versa. Here we test this potential mechanism physically using a robotic system. Local humidity measurements provide a cue for material deposition. As the analogue of the termite's deposition of wet soil and corresponding local increase in humidity, the robot drips water onto an absorbent substrate as it moves. Results show that the robot extends a semi-enclosed area outward when air is undisturbed, but closes it off when air is disturbed by an external fan, consistent with termite building activity in still vs. windy conditions. This result demonstrates an example of adaptive construction patterns arising from the proposed coordination mechanism, and supports the hypothesis that such a mechanism operates in termites.

Research in autonomous robots for construction has largely focused on ground-based robots whose reach constrains the size of what they can build, or on climbing or aerial robots that build solid or unroofed structures. Autonomous construction of larger, multistory buildings, or bridges spanning unsupported distances, would require robots that build sturdy structures supporting their own weight. In this paper, we present VaultBot, a system of autonomous robots that build a load-bearing spanning vault using identical modular blocks. The custom blocks employ mechanical and other features to facilitate robotic manipulation and locomotion, and can be removed from and replaced in an assembled structure as a way of repairing damage. We characterize the system's performance and failure modes, and demonstrate reliable autonomous assembly for a structure composed of 46 blocks. Blocks can be made collapsible and deployable as a way of reducing mass and volume that must be transported to a construction site. Such a system could be used to help enable construction of protective shelters in challenging environments, such as disaster relief scenarios, arctic settings, or extraterrestrial habitats.

We present a decentralized control algorithm for robots to aid in carrying an unknown load. Coordination occurs solely through sensing of the forces on or movement of the shared load. Robots prevent undesired motion of the load while permitting movement in the task-relevant subspace, and stabilize against unexpected events by a transient decrease in compliance. The algorithm requires no direct communication between agents, and minimal knowledge of the system or task. We demonstrate the approach in simulation using a commercially available compliant robotic platform.

Advances in construction automation have tended to focus on either automating conventional earthmoving equipment or on the discrete assembly of superstructure elements. Neither paradigm has addressed anchoring introduced material into soil, a critical task for virtually all useful structures. Simple anchoring can be achieved by driving posts (discrete linear elements) or sheet piles (interlocking profiles) into the ground, serving as a foundation for a later superstructure. In this paper we present Romu, a wheeled robot that uses a combination of a vibratory hammer and its own body mass to drive both posts and piles into the ground. We report on the effects of hardware parameters on pile driving performance, and demonstrate operation in both controlled and natural environments. Romu is first configured to drive interlocking sheet piles. In addition to their utility as foundations, such walls could be useful directly as check dams, interventions used to prevent erosion and promote groundwater recharge in arid regions. We use simulations based on real-world terrains to explore the potential impact of a fleet of such robots deployed over a large watershed region, using a simple reactive approach to dynamically determine dam placement. Romu is then configured to drive a range of readily available building materials that commonly serve as posts. These include wooden slats that can be used for sand fencing, an intervention used to collect wind-blown sand to build barrier dunes. Post driving performance is characterized for a range of materials, and finally the use case of sand fencing is evaluated using physical tests at 1:10 scale in order to predict its potential impact. To broaden the utility of such robots in field settings, directions for future work include refinement of the hardware for improved operation in more terrains, increased capabilities for fuller autonomy, and integration with other construction tasks for more complex projects.

Termites in the genus Macrotermes construct large-scale soil mounds above their nests. The classic explanation for how termites coordinate their labour to build the mound, based on a putative cement pheromone, has recently been called into question. Here we present evidence for an alternate interpretation based on sensing humidity. The high humidity characteristic of the mound internal environment extends a short distance into the low-humidity external world, in a "bubble" that can be disrupted by external factors like wind. Termites transport more soil mass into on-mound reservoirs when shielded from water loss through evaporation, and into experimental arenas when relative humidity is held at a high value. These results suggest that the interface between internal and external conditions may serve as a template for mound expansion, with workers moving freely within a zone of high humidity and depositing soil at its edge. Such deposition of additional moist soil will increase local humidity, in a feedback loop allowing the "interior" zone to progress further outward and lead to mound expansion.

Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely "soft" (mathematical/computational modeling), "hard" (physical robots), and "wet" (chemical/biological systems) ALife. We also provide a classification to locate this research. Finally, we discuss the usefulness of self-organization and related concepts within ALife studies, point to perspectives and challenges for future research, and list open questions. We hope that this work will motivate discussions related to self-organization in ALife and related fields.

Real-world construction projects typically require three groups of tasks: site preparation (earthmoving, leveling), substructure (anchoring, foundations), and superstructure (load-bearing elements, facade, plumbing, wiring, etc.). Advances in construction automation have revealed a gap between industry and academic research, where industry efforts have been focused on automating conventional earthmoving equipment and embracing prefabrication in order to reduce the amount of work that needs to be done on site, while academic efforts have largely concentrated on proposals for on-site additive manufacturing or discrete assembly, which may be of limited applicability to industry. This review presents a broad range of advancements in construction automation research, and finds that achieving fully autonomous construction in unstructured environments will require considerably more development in all three groups of construction tasks, as well as a particular emphasis on coordinating myriad construction tasks between different task-specific robots. Consideration is given to both mature technologies (conventional equipment widely used in industry) and emerging technologies (novel machines designed for autonomy). Key findings from the survey suggest that achieving the goal of fully autonomous construction will require more attention to be paid to site preparation and substructure tasks, material-robot systems (co-designed robots and building materials), embedded sensing, auxiliary construction tasks, and coordinating operations between robot systems. More general lessons from the literature indicate that making incremental improvements to mature technologies may benefit the industry in the short term, but there are considerable limitations to adding autonomy to equipment designed for human operators. Instead, we perceive a demand for novel hardware to be developed for specific tasks, in each case based on fundamental principles and at the appropriate scale, as well as for an increase in interdisciplinary research. We suggest that the reported shortage of skilled labor in the industry can be met with an increased emphasis on training for leveraging advances in automation.

Macrotermes michaelseni and M. natalensis are two morphologically similar species occupying the same habitat across southern Africa. Both build large mounds and tend mutualistic fungal symbionts for nutrients, but despite these behavioural and physiological similarities, the mound superstructures they create differ markedly. The behavioural differences behind this discrepancy remain elusive, and are the subject of ongoing investigations. Here we show that the two species demonstrate distinctive building activity in a lab-controlled environment consisting of still air with low ambient humidity. In these conditions, M. michaelseni transports less soil from a central reservoir, deposits this soil over a smaller area, and creates structures with a smaller volumetric envelope than M. natalensis. In high humidity, no such systematic difference is observed. This result suggests a differential behavioural threshold or sensitivity to airborne moisture that may relate to the distinct macro-scale structures observed in the African bushland.

Multi-agent systems demonstrate the ability to collectively perform complex tasks (e.g., construction, search, and locomotion) with greater speed, efficiency, or effectiveness than could a single agent alone. Direct and indirect coordination methods allow agents to collaborate to share information and adapt their activity to fit dynamic situations. A well-studied example is quorum sensing (QS), a mechanism allowing bacterial communities to coordinate and optimize various phenotypes in response to population density. Here we implement, for the first time, bio-inspired QS in robots fabricated from DNA origami, which communicate by transmitting and receiving diffusing signals. The mechanism we describe includes features such as programmable response thresholds and quorum quenching, and is capable of being triggered by proximity of a specific target cell. Nanoscale robots with swarm intelligence could carry out tasks that have been so far unachievable in diverse fields such as industry, manufacturing, and medicine.

Soil stabilization is a fundamental component of nearly all construction projects, ranging from commercial construction to environmental restoration projects. Previous work in autonomous construction has generally not considered these essential stabilization and anchoring tasks. In this work we present Romu, an autonomous robot capable of building continuous linear structures by using a vibratory hammer to drive interlocking sheet piles into soil. We report on hardware parameters and their effects on pile driving performance, and demonstrate autonomous operation in both controlled and natural environments. Finally, we present simulations in which a small swarm of robots build with sheet piles in example terrains, or apply an alternate spray-based stabilizing agent, and quantify the ability of each intervention to mitigate hydraulic erosion.

Termite colonies construct towering, complex mounds, in a classic example of distributed agents coordinating their activity via interaction with a shared environment. The traditional explanation for how this coordination occurs focuses on the idea of a "cement pheromone", a chemical signal left with deposited soil that triggers further deposition. Recent research has called this idea into question, pointing to a more complicated behavioral response to cues perceived with multiple senses. In this work, we explored the role of topological cues in affecting early construction activity in Macrotermes. We created artificial surfaces with a known range of curvatures, coated them with nest soil, placed groups of major workers on them, and evaluated soil displacement as a function of location at the end of one hour. Each point on the surface has a given curvature, inclination, and absolute height; to disambiguate these factors, we conducted experiments with the surface in different orientations. Soil displacement activity is consistently correlated with surface curvature, and not with inclination nor height. Early exploration activity is also correlated with curvature, to a lesser degree. Topographical cues provide a long-term physical memory of building activity in a manner that ephemeral pheromone labeling cannot. Elucidating the roles of these and other cues for group coordination may help provide organizing principles for swarm robotics and other artificial systems.

Self-organization has been an important concept within a number of disciplines, which Artificial Life (ALife) also has heavily utilized since its inception.  The term and its implications, however, are often confusing or misinterpreted.  In this work, we provide a mini-review of self-organization and its relationship with ALife, aiming at initiating discussions on this important topic with the interested audience. We first articulate some fundamental aspects of self-organization, outline its usage, and review its applications to ALife within its soft, hard, and wet domains. We also provide perspectives for further research.