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Space telerobots and planetary rovers

Space telerobots and planetary rovers

引用

AIAA/NASA 1st international symposium on Space automation and robotics, 1988

作者： Ruoff, Carl F. Jet Propulsion Laboratory California Institute of Technology Space Robotics Research PasadenaCA United States

Space telerobots and planetary rovers are advanced forms of space automation that are being studied for missions beginning in the 1990's. This paper describes telerobots and planetary rovers, points out that pure autonomy is far beyond the state of the art, and goes on to discuss how useful, realizable telerobots and rovers can be developed in the context of human-machine systems. Telerobot and rover computational and architectural requirements are also briefly examined, and examples of current work, including the development of dedicated analog processing chips based upon neural networks are described. The paper closes with some speculations on the terrestrial implications of space robotics and some general conclusions. © 1988 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Rovers

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Model Predictive fuzzy Control of the Degree of automation Optimizing Robot Health 17

Model Predictive fuzzy Control of the Degree of Automation O...

引用

17th IEEE international symposium on Applied computational intelligence and Informatics, SACI 2023

作者： Braun, Christian Alexander Ramesh, Aniketh Rothfus, Simon Chiou, Manolis Stolkin, Rustam Hohmann, Soren Karlsruhe Institute of Technology Institute of Control Systems Karlsruhe Germany University of Birmingham Extreme Robotics Lab Birmingham United Kingdom

ISBN: (纸本)9798350321104

Adjusting operator support in human-machine systems is a promising way of combining operator involvement with high overall system performance. Adaptive automation aims to achieve this goal without burdening the operator with the task of selecting and setting the desired amount of support. In this work, two novel adaptive automations are presented. We use the performance measure of 'robot health' to formulate the optimal control problem of maximizing the robot health of a human-robot system through the adaption of operator support to develop two model predictive controllers. The first one considers discrete levels of operator support, or levels of automation, the second one uses the continuous conception of the degree of automation. We report on a proof-of-concept simulation study evaluating the proposed model predictive controllers in a collaborative teleoperation of a mobile robot;the results demonstrate the ability of both model predictive controllers to successfully arbitrate control between the operator and the robot's controller to maximize robot health. © 2023 IEEE.

关键词： Fuzzy control

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Reinforcement Learning of Depth Stabilization with a Micro Diving Agent

Reinforcement Learning of Depth Stabilization with a Micro D...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Brinkmann, Gerrit Bessa, Wallace M. Duecker, Daniel-A. Kreuzer, Edwin Solowjow, Eugen Hamburg Univ Technol Inst Mech & Ocean Engn Hamburg Germany Univ Fed Rio Grande do Norte Dept Mech Engn Natal RN Brazil Siemens Corp Technol Berkeley CA USA

ISBN: (纸本)9781538630815

Reinforcement learning (RL) allows robots to solve control tasks through interaction with their environment. In this paper we study a model-based value-function RL approach, which is suitable for computationally limited robots and light embedded systems. We develop a diving agent, which uses the RL algorithm for underwater depth stabilization. Simulations and experiments with the micro diving agent demonstrate its ability to learn the depth stabilization task.

关键词： computational modeling Learning (artificial intelligence) Task analysis Robot kinematics Heuristic algorithms Force"

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Koopman NMPC: Koopman-based Learning and Nonlinear Model Predictive Control of Control-affine Systems

Koopman NMPC: Koopman-based Learning and Nonlinear Model Pre...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Folkestad, Carl Burdick, Joel W. CALTECH Div Engn & Appl Sci Pasadena CA 91125 USA

ISBN: (纸本)9781728190778

Koopman-based learning methods can potentially be practical and powerful tools for dynamical robotic systems. However, common methods to construct Koopman representations seek to learn lifted linear models that cannot capture nonlinear actuation effects inherent in many robotic systems. This paper presents a learning and control methodology that is a first step towards overcoming this limitation. Using the Koopman canonical transform, control-affine dynamics can be expressed by a lifted bilinear model. The learned model is used for nonlinear model predictive control (NMPC) design where the bilinear structure can be exploited to improve computational efficiency. The benefits for control-affine dynamics compared to existing Koopman-based methods are highlighted through an example of a simulated planar quadrotor. Prediction error is greatly reduced and closed loop performance similar to NMPC with full model knowledge is achieved.

关键词： Learning systems Dictionaries System dynamics computational modeling Transforms Predictive models Tools

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Sampling-based Polytopic Trees for Approximate Optimal Control of Piecewise Affine Systems

Sampling-based Polytopic Trees for Approximate Optimal Contr...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Sadraddini, Sadra Tedrake, Russ MIT Comp Sci & Artificial Intelligence Lab 32 Vassar St Cambridge MA 02139 USA

ISBN: (纸本)9781538660263

Piecewise affine (PWA) systems are widely used to model highly nonlinear behaviors such as contact dynamics in robot locomotion and manipulation. Existing control techniques for PWA systems have computational drawbacks, both in offline design and online implementation. In this paper, we introduce a method to obtain feedback control policies and a corresponding set of admissible initial conditions for discrete-time PWA systems such that all the closed-loop trajectories reach a goal polytope, while a cost function is optimized. The idea is conceptually similar to LQR-trees [1], which consists of 3 steps: (1) open-loop trajectory optimization, (2) feedback control for computation of "funnels" of states around trajectories, and (3) repeating (1) and (2) in a way that the funnels are grown backward from the goal in a tree fashion and fill the state-space as much as possible. We show PWA dynamics can be exploited to combine step (1) and (2) into a single step that is tackled using mixed-integer convex programming, which makes the method suitable for dealing with hard constraints. Illustrative examples on contact-based dynamics are presented.

关键词： Trajectory Robots Programming Integrated circuit modeling Optimization Optimal control computational modeling

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Controller Synthesis for Discrete-time Hybrid Polynomial Systems via Occupation Measures

Controller Synthesis for Discrete-time Hybrid Polynomial Sys...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Han, Weiqiao Tedrake, Russ MIT Comp Sci & Artificial Intelligence Lab 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9781538660263

We consider the feedback design for stabilizing a rigid body system by making and breaking multiple contacts with the environment without prespecifying the timing or the number of occurrence of the contacts. We model such a system as a discrete-time hybrid polynomial system, where the state-input space is partitioned into several polytopic regions with each region associated with a different polynomial dynamics equation. Based on the notion of occupation measures, we present a novel controller synthesis approach that solves finite-dimensional semidefinite programs as approximations to an infinite-dimensional linear program to stabilize the system. The optimization formulation is simple and convex, and for any fixed degree of approximations the computational complexity is polynomial in the state and control input dimensions. We illustrate our approach on some robotics examples.

关键词： Aerospace electronics Switches Mathematical model Optimization Legged locomotion

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Hierarchical MCTS for Scalable Multi-Vessel Multi-Float Systems

Hierarchical MCTS for Scalable Multi-Vessel Multi-Float Syst...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： D'urso, Giovanni Lee, James Ju Heon Pizarro, Oscar Yoo, Chanyeol Fitch, Robert Univ Technol Sydney Sydney NSW 2007 Australia Univ Sydney Australian Ctr Field Robot Sydney NSW 2006 Australia

ISBN: (纸本)9781728190778

Systems of multiple low-cost, underactuated floats combined with fully actuated surface vessels can improve the scalability and cost-effectiveness of autonomous systems for marine science and environmental monitoring. Here, we consider a coordination problem where surface vessels must drop off floats at locations such that they are likely to drift to observe given points of interest, and later must pick up the floats for redeployment. We define the Multi-Vessel Multi-Float (MVMF) problem and present a hierarchical solution based on the Dec-MCTS algorithm. Our solution defines customised sampling, rollout, and action generation algorithms to accommodate the problem's large search space and provide computational performance sufficient for practical application. We report analytical and simulation results that demonstrate the computational efficiency of our method and validate its behaviour in practical problems. These results immediately enable field experiments to progress the development of this exciting concept in multi-robot marine systems.

关键词： automation Autonomous systems Simulation Scalability Conferences Search problems Oceanography

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Performance Metrics Calculation for Assembly Systems with Exponential Reliability Machines

Performance Metrics Calculation for Assembly Systems with Ex...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Bai, Yishu Zhang, Liang

ISBN: (纸本)9781728190778

Assembly systems are commonly seen in production practice, where multiple components are joined in a manufacturing process to make a final product. In this paper, a decomposition/aggregation-based method is presented to evaluate the performance metrics of assembly systems with machines following the exponential reliability model (either synchronous or asynchronous). In particular, we consider the assembly system with multiple merge operations, each connected to a single external component line. The idea of the proposed method is to decompose the assembly system into a set of virtual serial lines based on the overlapping decomposition technique, evaluate of the starvation and blockage of the merge operations, and recursively update of the virtual machines' parameters in the thus-obtained serial lines. Then, the performance metrics of the original assembly system can be approximated based on the corresponding machines and buffers in the virtual serial lines. Numerical experiments are carried out to justify the convergence and computational efficiency of the method, as well as to evaluate the approximation accuracy of the proposed algorithm.

关键词： Measurement Assembly systems Software packages Software algorithms Approximation algorithms computational efficiency Steady-state

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computational intelligence Method for Ship Trajectory Planning 21

Computational Intelligence Method for Ship Trajectory Planni...

引用

21st international Conference on Methods and Models in automation and robotics (MMAR)

作者： Mohamed-Seghir, Mostefa Gdynia Maritime Univ Dept Ship Automat 83 Morska Str PL-81225 Gdynia Poland

ISBN: (纸本)9781509018666

This paper addresses the problem of ship trajectory planning in a collision situation. The objectives of this paper are twofold. The first objective is to propose the optimal safe ship trajectory in collision situation is presented as multistage decision-making in a fuzzy environment. The second objective is to use method based on the neural network to determine a safe ship trajectory planning. The maneuverability parameters of the ship and the navigator's subjective assessment in making a decision are taken under consideration in the process model.

关键词： collision situation decision-making fuzzy set theory neural network ship trajectory

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Approximate Branch and Bound for Fast, Risk-Bound Stochastic Path Planning

Approximate Branch and Bound for Fast, Risk-Bound Stochastic...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Strawser, Daniel Williams, Brian MIT Comp Sci & Artificial Intelligence Lab 32 Vassar St Cambridge MA 02139 USA

ISBN: (纸本)9781538630815

Path planning under uncertainty is a difficult and often intractable problem. Autonomous agents must model and reason about complex stochastic processes to quickly derive high quality plans. Most approaches separate the model of uncertainty from the planning;a model is selected and then a controller derived. This work proposes an approach for fast path planning under uncertainty that scales the model of uncertainty such that good policies receive the most effort. To do this, we use an innovative form of the problem's chance constraint to formulate a convex, stochastic path planning problem from the non-convex problem. Next, a bound on the path's expected cost is developed that allows a trade-off between speed of computation and accuracy. The bound is trivially parallelized on a GPU. Finally, a modified branch and bound algorithm is introduced that scales computational effort for more promising solutions. The method is benchmarked against existing approaches including those using Boole's inequality, a MILP approach, and a parallelized sampling-based approach. It outperforms other approaches based on speed and the ability to meet the chance constraint while not being overly conservative.

关键词： computational modeling Stochastic processes Trajectory Uncertainty Planning Aerospace electronics"

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