A stable analytical solution method for car-like robot trajectory tracking and optimization

Majd, Keyvan; Razeghi-Jahromi, Mohammad; Homaifar, Abdollah

doi:10.1109/jas.2019.1911816

Cited by 28 publications

(12 citation statements)

References 15 publications

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“…Future studies will also be focused on enhancing autonomous exploration by using the IMU orientation data to develop an advanced scheme to control the flippers. To that end, the control scheme will be trained with a training data set obtained from an expert human-robot operator by utilizing supervised machine learning techniques, which effectively facilitates the robot's navigation in simple repeatable missions [52,53].…”

Section: Fig 30 the Robot Is Inspecting Areas Beneath A Scaffolded Pmentioning

confidence: 99%

Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions

et al. 2021

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Rescue robots are expected to carry out reconnaissance and dexterity operations in unknown environments comprising unstructured obstacles. Although a wide variety of designs and implementations have been presented within the field of rescue robotics, embedding all mobility, dexterity, and reconnaissance capabilities in a single robot remains a challenging problem. This paper explains the design and implementation of Karo, a mobile robot that exhibits a high degree of mobility at the side of maintaining required dexterity and exploration capabilities for urban search and rescue (USAR) missions. We first elicit the system requirements of a standard rescue robot from the frameworks of Rescue Robot League (RRL) of RoboCup and then, propose the conceptual design of Karo by drafting a locomotion and manipulation system. Considering that, this work presents comprehensive design processes along with detail mechanical design of the robot’s platform and its 7-DOF manipulator. Further, we present the design and implementation of the command and control system by discussing the robot’s power system, sensors, and hardware systems. In conjunction with this, we elucidate the way that Karo’s software system and human–robot interface are implemented and employed. Furthermore, we undertake extensive evaluations of Karo’s field performance to investigate whether the principal objective of this work has been satisfied. We demonstrate that Karo has effectively accomplished assigned standardized rescue operations by evaluating all aspects of its capabilities in both RRL’s test suites and training suites of a fire department. Finally, the comprehensiveness of Karo’s capabilities has been verified by drawing quantitative comparisons between Karo’s performance and other leading robots participating in RRL.

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Section: Fig 30 the Robot Is Inspecting Areas Beneath A Scaffolded Pmentioning

confidence: 99%

Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions

et al. 2021

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“…Kinematic Constraints in the OCP: The kinematic principle of each CAV is known as nonholonomic [59], [60], [61], [62], [63]. A common approach to describe the nonholonomic feature of vehicle kinematics is a single-track bicycle model, which is accurate when a CAV runs at not-too-high speeds without side slips [64], [65]. As a basic step, a Cartesian coordinate frame is set up with the intersection center taken as the original point (Fig.…”

Section: B Cooperative Trajectory Planningmentioning

confidence: 99%

Sharing Traffic Priorities via Cyber–Physical–Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse

Cao

Tang

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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Replacing traffic signals with roadside vehicle-toinfrastructure systems in the era of connected and autonomous vehicles (CAVs) is promising. Managing CAVs in a signal-free intersection, known as autonomous intersection management (AIM), controls the driving behavior of each intersection-traverse CAV to maximize the throughput. Although AIM improves the gross throughput, the fairness of each individual vehicle in its right of way is not seriously considered. This study sets up an AIM system in the cyber-physical-social space to trade traverse priorities quantitatively and fairly. To that end, one needs an AIM method that is optimal and stable, otherwise no convincing trades of traverse priorities could be made. This study proposes a near-optimal lane-free AIM method based on numerical optimal control, wherein log-exp functions are deployed to convexify nondifferentiable collision-avoidance constraints. Besides that, a parameterized social force model (SFM) is proposed to provide a tunable initial guess for numerical optimal control. By tuning the urgency weights in SFM, one may get cooperative trajectories in different homotopy classes, which are further utilized to decide the amount of virtual currency to reward those CAVs who tend to share their traverse priorities. The overall method improves the traverse throughput with individual fairness Manuscript

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“…The kinematics of mobile robot is described in Boukens et al (2019) and Keyvan et al (2020). The motion model of a dynamic obstacle can be expressed by the following differential equation, where (x, y) is the position, θ is the angle of the dynamic obstacle velocity, v is the velocity, k is the curvature, and ω is the angular velocity.…”

Section: Occupancy Grid Prediction Modelmentioning

confidence: 99%

Mobile Robot Path Planning Based on Time Taboo Ant Colony Optimization in Dynamic Environment

et al. 2021

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This article aims to improve the problem of slow convergence speed, poor global search ability, and unknown time-varying dynamic obstacles in the path planning of ant colony optimization in dynamic environment. An improved ant colony optimization algorithm using time taboo strategy is proposed, namely, time taboo ant colony optimization (TTACO), which uses adaptive initial pheromone distribution, rollback strategy, and pheromone preferential limited update to improve the algorithm's convergence speed and global search ability. For the poor global search ability of the algorithm and the unknown time-varying problem of dynamic obstacles in a dynamic environment, a time taboo strategy is first proposed, based on which a three-step arbitration method is put forward to improve its weakness in global search. For the unknown time-varying dynamic obstacles, an occupancy grid prediction model is proposed based on the time taboo strategy to solve the problem of dynamic obstacle avoidance. In order to improve the algorithm's calculation speed when avoiding obstacles, an ant colony information inheritance mechanism is established. Finally, the algorithm is used to conduct dynamic simulation experiments in a simulated factory environment and is compared with other similar algorithms. The experimental results show that the TTACO can obtain a better path and accelerate the convergence speed of the algorithm in a static environment and can successfully avoid dynamic obstacles in a dynamic environment.

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A stable analytical solution method for car-like robot trajectory tracking and optimization

Cited by 28 publications

References 15 publications

Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions

Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions

Sharing Traffic Priorities via Cyber–Physical–Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse

Mobile Robot Path Planning Based on Time Taboo Ant Colony Optimization in Dynamic Environment

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