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Discovering Closed-Loop Failures of Vision-Based controllers via Reachability Analysis

IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第5期8卷 2692-2699页

作者： Chakraborty, Kaustav Bansal, Somil Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA 90089 USA

Machine learning driven image-based controllers allow robotic systems to take intelligent actions based on the visual feedback from their environment. Understanding when these controllers might lead to system safety violations is important for their integration in safety-critical applications and engineering corrective safety measures for the system. Existing methods leverage simulation-based testing (or falsification) to find the failures of vision-based controllers, i.e., the visual inputs that lead to closed-loop safety violations. However, these techniques do not scale well to the scenarios involving high-dimensional and complex visual inputs, such as RGB images. In this work, we cast the problem of finding closed-loop vision failures as a Hamilton-Jacobi (HJ) reachability problem. Our approach blends simulation-based analysis with HJ reachability methods to compute an approximation of the backward reachable tube (BRT) of the system, i.e., the set of unsafe states for the system under vision-based controllers. Utilizing the BRT, we can tractably and systematically find the system states and corresponding visual inputs that lead to closed-loop failures. These visual inputs can be subsequently analyzed to find the input characteristics that might have caused the failure. Besides its scalability to high-dimensional visual inputs, an explicit computation of BRT allows the proposed approach to capture non-trivial system failures that are difficult to expose via random simulations. We demonstrate our framework on two case studies involving an RGB image-based neural network controller for (a) autonomous indoor navigation, and (b) autonomous aircraft taxiing.

关键词： Robots Visualization Safety Robot sensing systems Computational modeling Aircraft navigation Aircraft Robot Safety formal methods in robotics and automation optimization and optimal control vision-based navigation

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Perceptive Locomotion in Rough Terrain - Online Foothold optimization

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IEEE ROBOTICS AND AUTOMATION LETTERS 2020年第4期5卷 5370-5376页

作者： Jenelten, Fabian Miki, Takahiro Vijayan, Aravind E. Bjelonic, Marko Hutter, Marco Swiss Fed Inst Technol Robot Syst Lab CH-8092 Zurich Switzerland ANYbotics AG CH-8050 Oerlikon Switzerland

Compared to wheeled vehicles, legged systems have a vast potential to traverse challenging terrain. To exploit the full potential, it is crucial to tightly integrate terrain perception for foothold planning. We present a hierarchical locomotion planner together with a foothold optimizer that finds locally optimal footholds within an elevation map. The map is generated in real-time from on-board depth sensors. We further propose a terrain-aware contact schedule to deal with actuator velocity limits. We validate the combined locomotion pipeline on our quadrupedal robot ANYmal with a variety of simulated and real-world experiments. We show that our method can cope with stairs and obstacles of heights up to 33% of the robot's leg length.

关键词： Legged robots motion control optimization and optimal control foothold optimization perceptive locomotion

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Fifteen observations on the structure of energy-minimizing gaits in many simple biped models

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JOURNAL OF THE ROYAL SOCIETY INTERFACE 2011年第54期8卷 74-98页

作者： Srinivasan, Manoj Ohio State Univ Columbus OH 43210 USA

A popular hypothesis regarding legged locomotion is that humans and other large animals walk and run in a manner that minimizes the metabolic energy expenditure for locomotion. Here, using numerical optimization and supporting analytical arguments, I obtain the energy-minimizing gaits of many different simple biped models. I consider bipeds with point-mass bodies and massless legs, with or without a knee, with or without a springy tendon in series with the leg muscle and minimizing one of many different 'metabolic cost' models-correlated with muscle work, muscle force raised to some power, the Minetti-Alexander quasi-steady approximation to empirical muscle metabolic rate (from heat and ATPase activity), a new cost function called the 'generalized work cost' C-g having some positivity and convexity properties (and includes the Minetti-Alexander cost and the work cost as special cases), and generalizations thereof. For many of these models, walking-like gaits are optimal at low speeds and running-like gaits at higher speeds, so a gait transition is optimal. Minimizing the generalized work cost C-g appears mostly indistinguishable from minimizing muscle work for all the models. Inverted pendulum walking and impulsive running gaits minimize the work cost, generalized work costs C-g and a few other costs for the springless bipeds;in particular, a knee-torque-squared cost, appropriate as a simplified model for electric motor power for a kneed robot biped. Many optimal gaits had symmetry properties;for instance, the left stance phase was identical to the right stance phases. Muscle force-velocity relations and legs with masses have predictable qualitative effects, if any, on the optima. For bipeds with compliant tendons, the muscle work-minimizing strategies have close to zero muscle work (isometric muscles), with the springs performing all the leg work. These zero work gaits also minimize the generalized work costs C-g with substantial additive force or force rate costs,

关键词： legged locomotion walking and running optimization and optimal control minimize energy gaits metabolic cost

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Full-Pose Trajectory Tracking of Overactuated Multi-Rotor Aerial Vehicles With Limited Actuation Abilities

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IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第8期8卷 4951-4958页

作者： Hamandi, Mahmoud Al-Ali, Ismail Seneviratne, Lakmal Franchi, Antonio Zweiri, Yahya Khalifa Univ Dept Aerosp Engn Abu Dhabi 52799 U Arab Emirates Khalifa Univ Ctr Autonomous Robot Syst Abu Dhabi 52799 U Arab Emirates New York Univ Abu Dhabi Ctr Artificial Intelligence & Robot Abu Dhabi 129188 U Arab Emirates Khalifa Univ Dept Mech Engn Abu Dhabi 52799 U Arab Emirates Univ Twente Fac Elect Engn Math & Comp Sci Robot & Mechatron Lab NL-7500 AE Enschede Netherlands Sapienza Univ Rome Dept Comp Control & Management Engn I-00185 Rome Italy Univ Toulouse LAAS CNRS F-31000 Toulouse France Khalifa Univ Adv Res & Innovat Ctr Abu Dhabi 52799 U Arab Emirates

This letter presents a novel optimization-based full-pose trajectory tracking method to control overactuated multi-rotor aerial vehicles with limited actuation abilities. The proposed method allocates feasible control inputs to track a reference trajectory, while ensuring the tracking of the reference position, and while tracking the closest feasible attitude. The optimization simultaneously searches for a feasible trajectory and corresponding feasible control inputs from the infinite possible solutions, while ensuring smooth control inputs. The proposed real-time algorithm is tested in extensive simulation on multiple platforms with fixed and actuated propellers. The simulation experiments show the ability of the proposed approach to exploit the complex set of feasible forces and moments of overactuated platforms while allocating smooth feasible control inputs.

关键词： Aerial systems Applications aerial systems Mechanics and control optimization and optimal control

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Sparse optimization of Contact Forces for Balancing control of Multi-Legged Humanoids

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IEEE ROBOTICS AND AUTOMATION LETTERS 2019年第2期4卷 1117-1124页

作者： Polverini, Matteo Parigi Hoffman, Enrico Mingo Laurenzi, Arturo Tsagarakis, Nikos G. Ist Italiano Tecnol Adv Robot Dept I-16163 Genoa Italy Univ Genoa Dipartimento Informat Bioingn Robot & Ingn Sistem I-16126 Genoa Italy

Multi-legged humanoid platforms present an inherent redundancy in the number of end-effectors required to perform interaction tasks, such as balancing and manipulation. The most relevant possibility opened up by end-effector redundancy consists in using a subset of the available end-effectors to perform a primary task, while employing the remaining end-effectors to perform a secondary tasks. As a consequence, it necessarily requires a methodology to automatically find the smallest set of end-effectors required to perform a primary task. For the balancing control of a torque-controlled humanoid, this is equivalent to finding a sparse solution of a contact force distribution problem. To this end, two different sparse optimization approaches are presented and extensively discussed in this work. The effectiveness of the proposed approaches has been validated on a simulated model of the CENTAURO robot developed at the Istituto Italiano di Tecnologia.

关键词： optimization and optimal control humanoid robots force control

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A Simulation-Based Metaheuristic Approach to Integrated Scheduling of Seedling Production

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IEEE ROBOTICS AND AUTOMATION LETTERS 2022年第2期7卷 1792-1799页

作者： Feng, Jingyuan Hu, Xiangpei Kong, Nan Dalian Univ Technol Sch Econ & Management Dalian 116024 Liaoning Peoples R China Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47906 USA

Seedling production is important to modern agriculture for its economic value in land utilization and yield promotion. Three crucial decisions for seedling production are new order acceptance, backlogged order fulfillment, and growth rate control. The first decision is made in an on-line fashion whenever a new order arrives, whereas the subsequent two decisions are made periodically. Given the interplay between the three operations and requirements on the heterogeneous frequency of the decisions, many analytical methods lack sufficient flexibility to deal with the problem and difficult to apply in practice. In this letter, we propose a simulation-based metaheuristic optimization approach to identify the appropriate policy for the above decisions, including a fine-grained simulation model for a representative seedling production process, heuristic decision rules on each of the decisions, and a particle swarm optimization algorithm embeds an optimal computing budget allocation scheme to explore the rules combination space efficiently. Through numerical experiments, we justify the viability of our metaheuristic algorithm;show the superiority of our backlog order fulfillment rules over two benchmark sequential dispatching rules;also demonstrate the economic benefit to periodically regulate the production rate rather than keep in invariant rate. Our work presents a novel application of simulation optimization to smart seedling production operations management.

关键词： optimization and optimal control integrated planning and control sustainable production and service automation commercial seedling production simulation-based metaheuristic

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Development and Experimental Evaluation of Concurrent control of a Robotic Arm and Continuum Manipulator for Osteolytic Lesion Treatment

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IEEE ROBOTICS AND AUTOMATION LETTERS 2017年第3期2卷 1625-1631页

作者： Wilkening, Paul Alambeigi, Farshid Murphy, Ryan J. Taylor, Russell H. Armand, Mehran Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Dept Mech Engn Baltimore MD 21218 USA Johns Hopkins Univ Appl Phys Lab Dept Res & Exploratory Dev Johns Hopkins Rd Laurel MD 20723 USA

This letter presents the development and evaluation of concurrent control of a robotic system for less-invasive treatment of osteolytic lesions behind an acetabular implant. This system implements safety constraints including a remote center of motion, virtual walls, and joint limits while operating through the screw holes of the acetabular implant. The formulated linear constrained optimization problem ensures these constraints are satisfied while maintaining precise control of the tip of a Continuum Dexterous Manipulator attached to a positioning robot. Experiments evaluated the performance of the tip control method within an acetabular cup. The controller reliably reached a series of goal points with a mean error of 0.42 mm and a worst-case error of straying 1.0 mm from our path.

关键词： Dexterous manipulation medical robots and systems optimization and optimal control

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Planning of Heterogeneous Multi-Agent Systems Under Signal Temporal Logic Specifications With Integral Predicates

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IEEE ROBOTICS AND AUTOMATION LETTERS 2021年第2期6卷 1375-1382页

作者： Buyukkocak, Ali Tevfik Aksaray, Derya Yazcoglu, Yasin Univ Minnesota Dept Aerosp Engn & Mech Minneapolis MN 55455 USA Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

We address the problem of coordinating the trajectories of heterogeneous multi-agent systems under spatio-temporal specifications. In particular, we consider global Signal Temporal Logic (STL) constraints to express the number and type of agents that should be present at specific locations within the desired time windows. We also introduce an integral predicate to specify cumulative progress that can he achieved asynchronously by multiple agents. In order to generate optimal trajectories, we formulate a mixed-integer linear program whose objective is minimizing the agent movement subject to the heterogeneous abstracted dynamics of the agents and a global STL specification including the novel integral predicate. We demonstrate the performance of the proposed method via simulations and experiments with drones.

关键词： Formal methods in robotics and automation multi-robot systems optimization and optimal control

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Enhancement of Force Exertion Capability of a Mobile Manipulator by Kinematic Reconfiguration

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IEEE ROBOTICS AND AUTOMATION LETTERS 2020年第4期5卷 5842-5849页

作者： Xing, Hongjun Torabi, Ali Ding, Liang Gao, Haibo Deng, Zongquan Tavakoli, Mahdi Harbin Inst Technol State Key Lab Robot & Syst Harbin 150001 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 1H9 Canada

With the increasing applications of wheeled mobile manipulators (WMMs), new challenges have arisen in terms of executing high-force tasks while maintaining precise trajectory tracking. A WMM, which consists of a manipulator mounted on a mobile base, is often a kinematically redundant robot. The existing WMM configuration optimization methods for redundant WMMs are conducted in the null-space of the entire system. Such methods do not consider the differences between the mobile base and the manipulator, such as their different kinematics, dynamics, or operating conditions. This may inevitably reduce the force exertion capability and degrade the tracking precision of the WMM. To enhance the force exertion capability of a WMM, this letter maximizes the directional manipulability (DM) of the manipulator, with consideration of the joint torque differences, first in Cartesian space and then in the null-space of the robotic system. To maintain precise end-effector trajectory tracking, this letter proposes a novel coordination method between the mobile base and the manipulator via a weighting matrix. The advantages and effectiveness of the proposed approach are demonstrated through experiments.

关键词： Mobile manipulation wheeled robots kinematics redundant robots optimization and optimal control

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Isolating Trajectory Tracking From Motion control: A Model Predictive control and Robust control Framework for Unmanned Ground Vehicles

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IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第3期8卷 1699-1706页

作者： Song, Jiarui Tao, Gang Zang, Zheng Dong, Haotian Wang, Boyang Gong, Jianwei Beijing Inst Technol Intelligent Vehicle Res Ctr Sch Mech Engn Beijing 100081 Peoples R China

This letter studies the trajectory tracking and motion control problems of unmanned ground vehicles (UGVs). A model predictive control and robust control (MPC-RC) framework for UGVs is proposed to improve tracking accuracy, yaw stability and robustness in a modular fashion without introducing complexity into controller. The trajectory tracking problem and three-dimensional phase trajectory planning with high stability of a vehicle motion can be performed in the model predictive control design simultaneously. Also, combining the advantages of linear matrix inequality, sliding mode control, and back-stepping control law, three robust motion controllers can track the generated three-dimensional phase trajectory steadily so that the UGV motion stability is guaranteed. The robust performance is guaranteed through considering model uncertainties and terra-aerodynamic disturbances in robust controllers. Sufficient conditions for closed-loop stability under the diverse robust factors are provided by the Lyapunov method analytically, which ensures the series system's feasibility. The results of simulations on MATLAB-Carsim platform demonstrate that the proposed controller can significantly enhance tracking accuracy, motion stability, and robustness compared to the existing methods, which guarantees the feasibility and capability of driving in a nonlinear extreme scenario.

关键词： Vehicle dynamics Tires Wheels Trajectory tracking Mathematical models Stability criteria Robustness Autonomous vehicle navigation optimization and optimal control robust adaptive control

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