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1. Obstacle Avoidance Path Planning for Worm-like Robot Using Bézier Curve

   https://doi.org/10.3390/biomimetics6040057  

   Wang, Yifan ; Liu, Zehao ; Kandhari, Akhil ; Daltorio, Kathryn A. ( December 2021 , Biomimetics)

   Worm-like robots have demonstrated great potential in navigating through environments requiring body shape deformation. Some examples include navigating within a network of pipes, crawling through rubble for search and rescue operations, and medical applications such as endoscopy and colonoscopy. In this work, we developed path planning optimization techniques and obstacle avoidance algorithms for the peristaltic method of locomotion of worm-like robots. Based on our previous path generation study using a modified rapidly exploring random tree (RRT), we have further introduced the Bézier curve to allow more path optimization flexibility. Using Bézier curves, the path planner can explore more areas and gain more flexibility to make the path smoother. We have calculated the obstacle avoidance limitations during turning tests for a six-segment robot with the developed path planning algorithm. Based on the results of our robot simulation, we determined a safe turning clearance distance with a six-body diameter between the robot and the obstacles. When the clearance is less than this value, additional methods such as backward locomotion may need to be applied for paths with high obstacle offset. Furthermore, for a worm-like robot, the paths of subsequent segments will be slightly different than the path of the head segment. Here,more »we show that as the number of segments increases, the differences between the head path and tail path increase, necessitating greater lateral clearance margins.« less
2. Design and Actuation of a Fabric-Based Worm-Like Robot

   https://doi.org/10.3390/biomimetics4010013  

   Kandhari, Akhil ; Mehringer, Anna ; Chiel, Hillel J. ; Quinn, Roger D. ; Daltorio, Kathryn A. ( March 2019 , Biomimetics)

   Soft-bodied animals, such as earthworms, are capable of contorting their body to squeeze through narrow spaces, create or enlarge burrows, and move on uneven ground. In many applications such as search and rescue, inspection of pipes and medical procedures, it may be useful to have a hollow-bodied robot with skin separating inside and outside. Textiles can be key to such skins. Inspired by earthworms, we developed two new robots: FabricWorm and MiniFabricWorm. We explored the application of fabric in soft robotics and how textile can be integrated along with other structural elements, such as three-dimensional (3D) printed parts, linear springs, and flexible nylon tubes. The structure of FabricWorm consists of one third the number of rigid pieces as compared to its predecessor Compliant Modular Mesh Worm-Steering (CMMWorm-S), while the structure of MiniFabricWorm consists of no rigid components. This article presents the design of such a mesh and its limitations in terms of structural softness. We experimentally measured the stiffness properties of these robots and compared them directly to its predecessors. FabricWorm and MiniFabricWorm are capable of peristaltic locomotion with a maximum speed of 33 cm/min (0.49 body-lengths/min) and 13.8 cm/min (0.25 body-lengths/min), respectively.
3. Spiking Neural Networks Through the Lens of Streaming Algorithms

   Hitron, Y. ; Musco, C. ; Parter, M. ( January 2020 , 34th International Symposium on Distributed Computing (DISC))

   We initiate the study of biologically-inspired spiking neural networks from the perspective of streaming algorithms. Like computers, human brains face memory limitations, which pose a significant obstacle when processing large scale and dynamically changing data. In computer science, these challenges are captured by the well-known streaming model, which can be traced back to Munro and Paterson `78 and has had significant impact in theory and beyond. In the classical streaming setting, one must compute a function f of a stream of updates 𝒮 = {u₁,…,u_m}, given restricted single-pass access to the stream. The primary complexity measure is the space used by the algorithm. In contrast to the large body of work on streaming algorithms, relatively little is known about the computational aspects of data processing in spiking neural networks. In this work, we seek to connect these two models, leveraging techniques developed for streaming algorithms to better understand neural computation. Our primary goal is to design networks for various computational tasks using as few auxiliary (non-input or output) neurons as possible. The number of auxiliary neurons can be thought of as the "space" required by the network. Previous algorithmic work in spiking neural networks has many similarities with streaming algorithms.more »However, the connection between these two space-limited models has not been formally addressed. We take the first steps towards understanding this connection. On the upper bound side, we design neural algorithms based on known streaming algorithms for fundamental tasks, including distinct elements, approximate median, and heavy hitters. The number of neurons in our solutions almost match the space bounds of the corresponding streaming algorithms. As a general algorithmic primitive, we show how to implement the important streaming technique of linear sketching efficiently in spiking neural networks. On the lower bound side, we give a generic reduction, showing that any space-efficient spiking neural network can be simulated by a space-efficient streaming algorithm. This reduction lets us translate streaming-space lower bounds into nearly matching neural-space lower bounds, establishing a close connection between the two models.« less
4. An Analysis of Peristaltic Locomotion for Maximizing Velocity or Minimizing Cost of Transport of Earthworm-Like Robots

   https://doi.org/10.1089/soro.2020.0021  

   Kandhari, Akhil ; Wang, Yifan ; Chiel, Hillel J. ; Quinn, Roger D. ; Daltorio, Kathryn A. ( August 2020 , Soft Robotics)

   Earthworm-like peristaltic locomotion has been implemented in >50 robots, with many potential applications in otherwise inaccessible terrain. Design guidelines for peristaltic locomotion have come from observations of biology, but robots have empirically explored different structures, actuators, and control waveform shapes than those observed in biological organisms. In this study, we suggest a template analysis based on simplified segments undergoing beam deformations. This analysis enables calculation of the minimum power required by the structure for locomotion and maximum speed of locomotion. Thus, design relationships are shown that apply to peristaltic robots and potentially to earthworms. Specifically, although speed is maximized by moving as many segments as possible, cost of transport (COT) is optimized by moving fewer segments. Furthermore, either soft or relatively stiff segments are possible, but the anisotropy of the stiffnesses is important. Experimentally, we show on our earthworm robot that this method predicts which control waveforms (equivalent to different gaits) correspond to least input power or to maximum velocity. We extend our analysis to 150 segments (similar to that of earthworms) to show that reducing COT is an alternate explanation for why earthworms have so few moving segments. The mathematical relationships developed here between structural properties, actuation power, andmore »waveform shape will enable the design of future robots with more segments and limited onboard power.« less
5. Towards a Unified Planner For Socially-Aware Navigation

   Banisetty, S. ; Feil-Seifer, D. ( November 2018 , AAAI Fall Symposium Series: AI-HRI Artificial Intelligence for Human-Robot Interaction)

   This paper presents a novel architecture to attain a Unified Planner for Socially-aware Navigation (UP-SAN) and explains its need in Socially Assistive Robotics (SAR) applications. Our approach emphasizes interpersonal distance and how spatial communication can be used to build a unified planner for a human-robot collaborative environment. Socially-Aware Navigation (SAN) is vital to make humans feel comfortable and safe around robots, HRI studies have show that the importance of SAN transcendent safety and comfort. SAN plays a crucial role in perceived intelligence, sociability and social capacity of the robot thereby increasing the acceptance of the robots in public places. Human environments are very dynamic and pose serious social challenges to the robots indented for human interactions. For the robots to cope with the changing dynamics of a situation, there is a need to infer intent and detect changes in the interaction context. SAN has gained immense interest in the social robotics community; to the best of our knowledge, however, there is no planner that can adapt to different interaction contexts spontaneously after autonomously sensing that context. Most of the recent efforts involve social path planning for a single context. In this work, we propose a novel approach for a Unifiedmore »Planner for SAN that can plan and execute trajectories that are human-friendly for an autonomously sensed interaction context. Our approach augments the navigation stack of Robot Operating System (ROS) utilizing machine learn- ing and optimization tools. We modified the ROS navigation stack using a machine learning-based context classifier and a PaCcET based local planner for us to achieve the goals of UP- SAN. We discuss our preliminary results and concrete plans on putting the pieces together in achieving UP-SAN.« less