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Learning to Locomote with Deep Neural-Network and CPG-based Control in a Soft Snake Robot

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arXiv 2020年

作者： Liu, Xuan Gasoto, Renato Jiang, Ziyi Onal, Cagdas Fu, Jie Robotics Engineering program at Worcester Polytechnic Institute RNVIDIA Electronic Engineering program Xidian University

In this paper, we present a new locomotion control method for soft robot snakes. Inspired by biological snakes, our control architecture is composed of two key modules: A deep reinforcement learning (RL) module for achieving adaptive goal-tracking behaviors with changing goals, and a central pattern generator (CPG) system with Matsuoka oscillators for generating stable and diverse locomotion patterns. The two modules are interconnected into a closed-loop system: The RL module, analogizing the locomotion region located in the midbrain of vertebrate animals, regulates the input to the CPG system given state feedback from the robot. The output of the CPG system is then translated into pressure inputs to pneumatic actuators of the soft snake robot. Based on the fact that the oscillation frequency and wave amplitude of the Matsuoka oscillator can be independently controlled under different time scales, we further adapt the option-critic framework to improve the learning performance measured by optimality and data efficiency. The performance of the proposed controller is experimentally validated with both simulated and real soft snake robots. Copyright © 2020, The Authors. All rights reserved.

关键词： Adaptive control systems

Human-Robot Shared Control for Surgical Robot Based on Context-Aware Sim-to-Real Adaptation

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arXiv 2022年

作者： Zhang, Dandan Wu, Zicong Chen, Junhong Zhu, Ruiqi Munawar, Adnan Xiao, Bo Guan, Yuan Su, Hang Hong, Wuzhou Guo, Yao Fischer, Gregory S. Lo, Benny Yang, Guang-Zhong The Department of Engineering Mathematics University of Bristol United Kingdom The Bristol Robotics Lab United Kingdom The Hamlyn Centre for Robotic Surgery Imperial College London United Kingdom The Department of Electronics Polytechnic University of Milan Italy The Institute of Medical Robotics Shanghai Jiao Tong University China The Worcester Polytechnic Institute United States

Human-robot shared control, which integrates the advantages of both humans and robots, is an effective approach to facilitate efficient surgical operation. Learning from demonstration (LfD) techniques can be used to automate some of the surgical subtasks for the construction of the shared control framework. However, a sufficient amount of data is required for the robot to learn the manoeuvres. Using a surgical simulator to collect data is a less resource-demanding approach. With sim-to-real adaptation, the manoeuvres learned from a simulator can be transferred to a physical robot. To this end, we propose a sim-to-real adaptation method to construct a human-robot shared control framework for robotic surgery. In this paper, a desired trajectory is generated from a simulator using LfD method, while dynamic motion primitive (DMP) based method is used to transfer the desired trajectory from the simulator to the physical robotic platform. Moreover, a role adaptation mechanism is developed such that the robot can adjust its role according to the surgical operation contexts predicted by a neural network model. The effectiveness of the proposed framework is validated on the da Vinci Research Kit (dVRK). Results of the user studies indicated that with the adaptive human-robot shared control framework, the path length of the remote controller, the total clutching number and the task completion time can be reduced significantly. The proposed method outperformed the traditional manual control via teleoperation. Copyright © 2022, The Authors. All rights reserved.

关键词： Robotic surgery

Stability and electronic properties of edges of SnS2

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Physical Review B 2020年第15期102卷 155306-155306页

作者： Tao Yan Pratap M. Rao N. Aaron Deskins Materials Science and Engineering program Worcester Polytechnic Institute Worcester Massachusetts 01609 USA Department of Mechanical Engineering Worcester Polytechnic Institute Worcester Massachusetts 01609 USA Department of Chemical Engineering Worcester Polytechnic Institute Worcester Massachusetts 01609 USA

Because of its two-dimensional structure and semiconducting properties, tin disulfide (SnS2) is of interest for many applications, such as photocatalysis, photovoltaics, sensing, and electronics. While the atomic and electronic structure of bulk and monolayer SnS2 have been studied, much less is known about the edges of layers. Such edges could have a major influence on the performance of SnS2. This paper reports on density functional theory (DFT) simulations of the atomic and electronic structure of the edges of SnS2. We modeled several different edge terminations at various S coverages and orientations, as well as performed thermodynamic analysis of edge terminations. Our results show that edges with 0% and 50% S atoms are most stable and that higher S coverage are unstable. We directly link edge stability with environmental temperature and pressure, which will guide the experimental synthesis of SnS2 materials. We found all the edges to be semiconducting, unlike other metal chalcogenides, and that the band gap energy decreased with increasing S coverage. Semiconducting edges could lead to lower charge recombination rates and better photocatalytic performance. Our calculations also show that edges may have direct or indirect band gaps, depending on the edge termination. Finally, we examined the reactivity of edges through hydrogen dissociation and found edges to be more reactive than basal planes. Our work provides important details on the nature of SnS2 edges and how these edges influence the electrical and chemical features of SnS2.

关键词： Dichalcogenides Surfaces Density functional theory

Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing

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Rearranging the Environment to Maximize Energy with a Roboti...

IEEE International Conference on robotics and Biomimetics

作者： Xianglong Tan Zhikang Liu Chen Yu Sören Schwertfeger Andre Rosendo Hamlyn Centre Imperial College London UK Department of Computer Science University of York UK School of Information Science and Technology ShanghaiTech University China Robotics Engineering Worcester Polytechnic Institute USA

ISBN: (纸本)9781665481106

The ability of acquiring energy form environments is greatly beneficial for robot to function in uncertain environments. In this work, we present a robot capable of drawing circuits with conductive ink while also rearranging the visual world to receive maximum energy from a power source. A range of circuit drawing tasks is designed to simulate real-world scenarios, including avoiding physical obstacles and regions that would discontinue drawn circuits. We adopt the state-of-the-art Transporter networks for pick-and-place manipulation from visual observation. We conduct experiments in both simulation and real-world settings, and our results show that, with a small number of demonstrations, the robot learns to rearrange the placement of objects (removing obstacles and bridging areas unsuitable for drawing) and to connect a power source with a minimum amount of conductive ink. As autonomous robots become more and more involved in our daily lives, our proposed approach brings a novel way for machines to keep themselves functional by rearranging their surroundings to create their own electric circuits.

关键词： Training Visualization Power supplies Planets Surface resistance Ink Machine learning

A theory of hypergames on graphs for synthesizing dynamic cyber defense with deception

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arXiv 2020年

作者： Kulkarni, Abhishek N. Fu, Jie Robotics Engineering Program Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA United States Dept. of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA United States

In this chapter, we present an approach using formal methods to synthesize reactive defense strategy in a cyber network, equipped with a set of decoy systems. We first generalize formal graphical security models–attack graphs–to incorporate defender’s countermeasures in a game-theoretic model, called an attack-defend game on graph. This game captures the dynamic interactions between the defender and the attacker and their defense/attack objectives in formal logic. Then, we introduce a class of hypergames to model asymmetric information created by decoys in the attacker-defender interactions. Given qualitative security specifications in formal logic, we show that the solution concepts from hypergames and reactive synthesis in formal methods can be extended to synthesize effective dynamic defense strategy using cyber deception. The strategy takes the advantages of the misperception of the attacker to ensure security specification is satisfied, which may not be satisfiable when the information is symmetric. Copyright © 2020, The Authors. All rights reserved.

关键词： Network security

Improved Performance of a Multipinhole SPECT for DAT Imaging by Increasing Number of Pinholes at the Expense of Increased Multiplexing

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Improved Performance of a Multipinhole SPECT for DAT Imaging...

作者： Konik, Arda Zeraatkar, Navid Kalluri, Kesava S. Auer, Benjamin Fromme, Timothy J. He, Yulun May, Micaehla Furenlid, Lars R. Kuo, Phillip H. King, Michael A. Department of Imaging Dana Farber Cancer Institute BostonMA02215 United States Department of Radiology University of Massachusetts Medical School WorcesterMA01605 United States Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Department of Computer Science MD Anderson Cancer Center HoustonTX United States Department of Radiology University of Arizona TucsonAZ85724 United States

Single photon emission tomography imaging of dopamine transporters (DATs) in the brain is a widely utilized study to improve the diagnosis of Parkinsonian syndromes, where conventional (parallel-hole and fan-beam) collimators on dual-head scanners are commonly employed. We have designed a multipinhole (MPH) collimator to improve the performance of DAT imaging. The MPH collimator focuses on the striatum and hence offers a better tradeoff for sensitivity and spatial resolution than the conventional collimators within this clinically most relevant region for DAT imaging. Our original MPH design consisted of 9 pinholes with a background-to-striatal (Bkg/Str) projection multiplexing of 1% only. In this simulation study, we investigated whether further improvements in the performance of MPH imaging could be obtained by increasing the number of pinholes, hence by enhancing the sensitivity and sampling, despite the ambiguity in reconstructing images due to increased multiplexing. We performed analytic simulations of the MPH configurations with 9, 13, and 16 pinholes (aperture diameters: 4-6 mm) using a digital phantom modeling DAT imaging. Our quantitative analyses indicated that using 13 (Bkg/Str: 12%) and 16 (Bkg/Str: 22%) pinholes provided better performance than the original 9-pinhole configuration for the acquisition with two or four angular views, but a similar performance with 8 and 16 views. © 2017 IEEE.

关键词： Photons

Reward engineering for Object Pick and Place Training

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arXiv 2020年

作者： Nagpal, Raghav Krishnan, Achyuthan Unni Yu, Hanshen Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Mechanical Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States

—Robotic grasping is a crucial area of research as it can result in the acceleration of the automation of several Industries utilizing robots ranging from manufacturing to healthcare. Reinforcement learning is the field of study where an agent learns a policy to execute an action by exploring and exploiting rewards from an environment. Reinforcement learning can thus be used by the agent to learn how to execute a certain task, in our case grasping an object. We have used the Pick and Place environment provided by OpenAI’s Gym to engineer rewards. Hindsight Experience Replay (HER) has shown promising results with problems having a sparse reward. In the default configuration of the OpenAI baseline and environment the reward function is calculated using the distance between the target location and the robot end-effector. By weighting the cost based on the distance of the end-effector from the goal in the x,y and z-axes we were able to almost halve the learning time compared to the baselines provided by OpenAI, an intuitive strategy that further reduced learning time. In this project, we were also able to introduce certain user desired trajectories in the learnt policies (city-block / Manhattan trajectories). This helps us understand that by engineering the rewards we can tune the agent to learn policies in a certain way even if it might not be the most optimal but is the desired manner. Copyright © 2020, The Authors. All rights reserved.

关键词： End effectors

Metabolic energy expenditure for time-varying isometric forces

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arXiv 2024年

作者： Muralidhar, Sriram Sekaripuram Heitman, Kristen Walcott, Samuel C. Srinivasan, Manoj Mechanical and Aerospace Engineering The Ohio State University ColumbusOH43201 United States School of Health and Rehabilitation Sciences The Ohio State University ColumbusOH43201 United States Mathematical Sciences and Bioinformatics and Computational Biology Worcester Polytechnic Institute WorcesterMA01609 United States Program in Biophysics The Ohio State University ColumbusOH43201 United States

Muscles consume metabolic energy (ATP) to produce force. A mathematical model for energy expen- diture can be useful in estimating real-time costs of movements or to predict energy optimal movements. Metabolic cost models developed so far have predominantly aimed at dynamic movement tasks, where me- chanical work dominates. Further, while it is known that both force magnitude and rate of change of force (force rate) affect metabolic cost, it is not known how these terms interact, or if the force rate dependence can be a consequence of the force dependence. Here, we performed extensive human subject experiments, involving each subject over 5 hours of metabolic trials, which systematically changed the mean forces and forces rates so as to characterize a holistic relation for metabolic cost based on both force and force rate - or analogously, torque and torque rate. Our experiments involved humans producing symmetric or asym- metric sinusoidal forces with different means, amplitudes, frequencies, and rise and fall periods. We showed that the metabolic cost can be well-approximated by a sum of power law functions of torque and torque rate. We found that the metabolic cost scales non-linearly with joint torque (with exponent 1 = 1.36) and non-linearly with torque rate (with exponent 2 = 2.5). Surprisingly, the data suggested that the cost was roughly four times higher for decreasing the torque than increasing, mirroring the analogous ratio between the cost of positive and negative work. Using these metabolic cost relations, we show that if the metabolic cost scales with particular exponents with muscle force and force rates, the same exponents will be observed in multi-joint tasks with multiple muscles. Our new metabolic cost model involving both force and force rate will potentially allow better predictions of energy optimal movements and thus inform wearable robot design and analysis. © 2024, CC BY.

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Atlas Humanoid Robot Control with Flexible Finite State Machines for Playing Soccer

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Atlas Humanoid Robot Control with Flexible Finite State Mach...

IEEE Southeastcon

作者： Davis S. Catherman Jakub Tomasz Kaminski Aishwary Jagetia Robotics Engineering Worcester Polytechnic Institute Worcester Massachusetts USA

ISBN: (数字)9781728168616

ISBN: (纸本)9781728168623

This work concerns Atlas robot autonomously com-pleting core soccer tasks in a static environment. A soccer ball is localized using robot 2D and 3D perception. The target kicking position is reached in a collision-free manner using robot locomotion and navigation capabilities. The ball is kicked thanks to leg manipulation motion planning. Additionally, FlexBE is used to implement a user in the loop state machine. Generic custom open-source states are used throughout the project and their functionality is tested. An overview of subject-relevant literature, techniques used and experiments performed are provided. We also discuss the system and environment-based limitations in the core project areas.

关键词： Three-dimensional displays Two dimensional displays Humanoid robots Safety Collision avoidance Task analysis Sports