Soft compliant microrobots have the potential to deliver significant societal impact when deployed in applications such as search and rescue. In this research we present mCLARI, a body compliant quadrupedal microrobot of 20mm neutral body length and 0.97g, improving on its larger predecessor, CLARI. This robot has four independently actuated leg modules with 2 degrees of freedom, each driven by piezoelectric actuators. The legs are interconnected in a closed kinematic chain via passive body joints, enabling passive body compliance for shape adaptation to external constraints. Despite scaling its larger predecessor down to 60 % in length and 38% in mass, mCLARI maintains 80% of the actuation power to achieve high agility. Additionally, we demonstrate the new capability of passively shape-morphing mCLARI - omnidirectional laterally confined locomotion - and experimentally quantify its running performance achieving a new unconstrained top speed of ~3 bodylengths/s (60 mms-1). Leveraging passive body compliance, mCLARI can navigate through narrow spaces with a body compression ratio of up to 1.5 × the neutral body shape.

Here we present HAMR-Jr, a 22.5mm, 320mg quadrupedal microrobot. With eight independently actuated degrees of freedom, HAMR-Jr is, to our knowledge, the most mechanically dexterous legged robot at its scale and is capable of high-speed locomotion (13.91bodylengthss-1) at a variety of stride frequencies (1-200Hz) using multiple gaits. We achieved this using a design and fabrication process that is flexible, allowing scaling with minimum changes to our workflow. We further characterized HAMR-Jr's open-loop locomotion and compared it with the larger scale HAMR-VI microrobot to demonstrate the effectiveness of scaling laws in predicting running performance.

We present an off-board phase estimator and controller for leg position near the resonance of the Harvard Ambulatory MicroRobot's (HAMR) two degree-of-freedom transmission. This control system is a first step towards leveraging the significant increase in stride length at transmission resonance for faster and more efficient locomotion. We experimentally characterize HAMR's transmission and determine that actuator phase is a sufficient proxy for leg phase across the range of useful operating frequencies (1-120Hz). An estimator is developed to determine actuator phase using off-board position sensors and it converges within a cycle on average. We also fit a nonlinear dynamic model of the transmission to the experimental data, and utilize the model to determine a suitable open-loop resonant leg trajectory and define feed forward control inputs. This resonant (100Hz) trajectory is theoretically 50% more efficient than pre-resonant high speed running trajectories. The controller converges to this trajectory in 0.05 ± 0.02 seconds (5.3 ± 2.4 cycles) in air, and in 0.05 ± 0.01 seconds (4.7 ± 0.6 cycles) under perturbations that approximate ground contact.

This paper develops a custom motion capture system that uses vision-based methods to rapidly and accurately track the body and leg position/orientation of a 1.43g legged microrobot, the Harvard Ambulatory MicroRobot (HAMR). Two new generalized metrics for quantifying locomotion performance are defined: amplitude-normalized stride correlation, and percent ineffective stance. Six different gaits are run on HAMR to validate the experimental setup and establish baseline performance. Furthermore, HAMR is compared with the cockroach, Blaberus Discoidalis, and with other legged robots. Future studies can leverage the experimental setup to study gait selection and transitions for small legged systems.