Half a century since the concept of a cyborg was introduced, digital cyborgs, enabled by the spread of wearable robotics, are the focus of much research in recent times. We introduce JIZAI ARMS, a supernumerary robotic limb system consisting of a wearable base unit with six terminals and detachable robot arms controllable by the wearer. The system was designed to enable social interaction between multiple wearers, such as an exchange of arm(s), and explore possible interactions between digital cyborgs in a cyborg society. This paper describes the JIZAI ARMS’ design process, an interdisciplinary collaboration between human augmentation researchers, product designers, a system architect, and manufacturers, to realize a technically complex system while considering the aesthetics of a digital cyborg. We also provide an autobiographical report of our first impressions of using the JIZAI ARMS and use our findings to speculate on a model of potential social interactions between digital cyborgs.

Locating a mobile target, untrackable in real-time, is pertinent to numerous time-critical applications, such as wilderness search and rescue. This paper proposes a hybrid approach to this dynamic problem, where both static and mobile sensors are utilized for the goal of detecting a target. The approach is novel in that a team of robots utilized to deploy a static-sensor network also actively searches for the target via on-board sensors. Synergy is achieved through: 1) optimal deployment planning of static-sensor networks and 2) optimal routing and motion planning of the robots for the deployment of the network and target search. The static-sensor network is planned first to maximize the likelihood of target detection while ensuring (temporal and spatial) unbiasedness in target motion. Robot motions are, subsequently, planned in two stages: 1) route planning and 2) trajectory planning. In the first stage, given a static-sensor network configuration, robot routes are planned to maximize the amount of spare time available to the mobile agents/sensors, for target search in between (just-in-time) static-sensor deployments. In the second stage, given robot routes (i.e., optimal sequences of sensor delivery locations and times), the corresponding robot trajectories are planned to make effective use of any spare time the mobile agents may have to search for the target. The proposed search strategy was validated through extensive simulations, some of which are given in detail here. An analysis of the method's performance in terms of target-search success is also included.

The search for a mobile target is a dynamic spatial and temporal problem. Information gathered during the search, regarding the potential whereabouts of the target, can be used to influence significantly the search strategy employed. In this paper, thus, a novel (wireless) static-sensor network deployment strategy is presented to detect efficiently and effectively a mobile target in an unbounded environment. The proposed strategy deploys the static sensors optimally and in a time-phased manner while adapting in real-time to the availability of new information during the search. An optimal network-deployment plan, herein, refers to a set of optimal sensor-deployment times and locations. The optimal sensor-deployment instances aim to achieve a uniform deployment of search effort over time. Optimal sensor-deployment locations, in turn, are determined according to the highest possible likelihood of detection of the mobile target. The proposed deployment strategy contains two novel contributions: it makes use of a non-parametric approach to estimate effectively the target location likelihood, and it performs an optimization of sensor-placement times to maximize the adaptive characteristic of the deployment plan. Several detailed experiments (in virtual and physical environments) of the proposed strategy for static-sensor network deployment in wilderness search and rescue applications are presented. Furthermore, a comparative study is included to highlight the advantages of our approach versus traditional methods that deploy sensors simultaneously for uniform coverage.

SUMMARY: The use of millirobots, particularly in swarm studies, would enable researchers to verify their proposed autonomous cooperative behavior algorithms under realistic conditions with a large number of agents. While multiple designs for such robots have been proposed, they, typically, require custom-made components, which make replication and manufacturing difficult, and, mostly, employ non-modular integral designs. Furthermore, these robots' proposed small sizes tend to limit sensory perception capabilities and operational time. Some have resolved few of the above issues through the use of extensions that, unfortunately, add to their size.In contribution to the pertinent field, thus, a novel millirobot with an open-source design, addressing the above concerns, is presented in this paper. Our proposed millirobot has a modular design and uses easy to source, off-the-shelf components. Themilli-robot-Toronto (mROBerTO) also includes a variety of sensors and has a 16 × 16 mm²footprint.mROBerTO's wireless communication capabilities include ANT^™, Bluetooth Smart, or both simultaneously. Data-processing is handled by an ARM processor with 256 KB of flash memory. Additionally, the sensing modules allow for extending or changing the robot's perception capabilities without adding to the robot's size. For example, the swarm-sensing module, designed to facilitate swarm studies, allows for measuring proximity and bearing to neighboring robots and performing local communications.Extensive experiments, some of which are presented herein, have illustrated the capability ofmROBerTOunits for use in implementing a variety of commonly proposed swarm algorithms.

Numerous millirobots were developed in the past decade for autonomous swarm systems that aim to utilize large numbers of these units in space-constrained environments. However, the size limitation of these robots has often resulted in their reduced computational, sensing, and locomotion capabilities. mROBerTO (milli-ROBot-TOronto) was developed in response to such limitations. Despite its enhanced features, the reliable and repeatable locomotion of mROBerTO has still been of some concern due to lack of effective closed-loop motion control – as is the case with all other similar millirobots. In this paper, we present the next version of mROBerTO with a new locomotion mechanism that utilizes stepper motors, capable of micro-stepping down to 1/32 of a full step, to yield a millirobot with maneuvering capabilities superior to current similar-sized robots. mROBerTO 2.0 is novel in that it utilizes these stepper motors without relying on a separate processor for controlling them. This paper also presents a complementary new algorithm for efficiently converting desired trajectories into robot-motion commands. The proposed algorithm was developed to allow millirobots to execute complex trajectories reliably in an open-loop manner.