Real-Time Optimal Trajectory Generation and Control of a Multi-Rotor With a Suspended Load for Obstacle Avoidance

Son, Clark Youngdong; Seo, Hoseong; Jang, Deok‐Jin; Kim, H. Jin

doi:10.1109/lra.2020.2967279

Cited by 23 publications

(9 citation statements)

References 17 publications

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“…The robot's motion is controlled according to the direction of the force. This method has a simple structure and smooth planning path, but its performance is poor in narrow areas, and it is easy to fall into the local optimal situation where the resultant force of the robot is zero, and it cannot continue to move forward to obtain the globally optimal path [9][10].…”

Section: Robot Path Planning Methodsmentioning

confidence: 99%

Path Avoidance System of Intelligent Robot Based on Computer Vision

Ren

2023

J. Phys.: Conf. Ser.

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At present, obstacle avoidance technology is widely used in the military field, scientific detection, traffic control, industrial manufacturing, medical service, and many other fields, and various machines with autonomous navigation and obstacle avoidance capabilities have been used to varying degrees, thus replacing some human daily production activities and bringing many conveniences to people’s lives. The key to autonomous obstacle avoidance is to obtain the direction information of the obstacle in its direction of advance in real time, which is also the precondition of obstacle avoidance system in obstacle avoidance path planning. In this paper, an intelligent robot path avoidance system is designed based on computer vision (CV) theory. The binocular vision ranging experiment verifies that the system has a less ranging error and can effectively detect the location of obstacles within a certain range, and the success rate of intelligent robot avoidance of obstacles reaches more than 96%, achieving a good avoidance effect.

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Section: Robot Path Planning Methodsmentioning

confidence: 99%

Path Avoidance System of Intelligent Robot Based on Computer Vision

Ren

2023

J. Phys.: Conf. Ser.

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“…This section describes how local reference trajectory is computed using MPC, which has been widely adopted in robotics as a real-time planner [17][18][19] thanks to its optimality and constraint-satisfying nature. The objective of this local receding-horizon planning is the following three: 1) physical constraint satisfaction, 2) disturbance-awareness, and 3) real-time computation.…”

Section: Local Planningmentioning

confidence: 99%

“…We use 9 Bernstein control points for phases 1 and 3, respectively, and 20 via points for phase 2. Next, to solve the formulated model predictive control problem (14), we implement differential dynamic programming (DDP) with augmented Lagrangian method [30], which is an algorithm widely exploited in various robotic application for real-time trajectory optimization [17][18][19]. It transforms the original constrained MPC problem into an unconstrained problem using the Lagrangian and quadratic penalty function, which is then solved with the conventional DDP algorithm.…”

Section: A Setupmentioning

confidence: 99%

Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

Lee¹,

Jang²,

Byun³

et al. 2021

Preprint

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Automation of excavation tasks requires real-time trajectory planning satisfying various constraints. To guarantee both constraint feasibility and real-time trajectory replannability, we present an integrated framework for realtime optimization-based trajectory planning of a hydraulic excavator. The proposed framework is composed of two main modules: a global planner and a real-time local planner. The global planner computes the entire global trajectory considering excavation volume and energy minimization while the local counterpart tracks the global trajectory in a receding horizon manner, satisfying dynamic feasibility, physical constraints, and disturbance-awareness. We validate the proposed planning algorithm in a simulation environment where two types of operations are conducted in the presence of emulated disturbance from hydraulic friction and soil-bucket interaction: shallow and deep excavation. The optimized global trajectories are obtained in an order of a second, which is tracked by the local planner at faster than 30 Hz. To the best of our knowledge, this work presents the first real-time motion planning framework that satisfies constraints of a hydraulic excavator, such as force/torque, power, cylinder displacement, and flow rate limits.

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“…An increase in the popularity of online shopping has been driving the development of aerial robots for efficient logistics management. Aerial robots are used for aerial delivery [1]- [4] or warehouse management [5]- [7]. However, several issues, such as safety and computational efficiency for path planning must be addressed to transport a bulky payload.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Generation of a Quadrotor Transporting a Bulky Payload in the Cluttered Environments

Lee

2022

IEEE Access

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When an aerial robot carries a bulky and heavy payload, it suffers from a wavering effect because of the large inertia of the heavy mass of a payload, which can cause a serious crash or fall to the ground. We propose the path-planning algorithm for an aerial robot to pass a narrow space while transporting a bulky payload to resolve the issue. Unlike the existing conventional path-planning method that treats the payload as a point-mass, this paper generates the trajectory considering the shape of a payload and passage size of an Unmanned Aerial Vehicle (UAV). First, we design a map-generation algorithm with the Voronoi diagram by exploiting the fact that the UAV has an ellipsoidal shape in transport operation with a bulky object. The modified map data can be exploited for the global path generation such as A* path-planner. For the rotational motion of the UAV, the heading angle was determined by considering the lengths of the major and minor axes of the ellipse. The global path was optimized based on the elastic band optimization algorithm to solve the jerky motion on the trajectory. Through the simulations and experiments, we validate the efficiency of our algorithm in the environment with the narrow space. Experimental results showed that the proposed path-planning algorithm could be used for safe aerial transportation in realistic environments.

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Real-Time Optimal Trajectory Generation and Control of a Multi-Rotor With a Suspended Load for Obstacle Avoidance

Cited by 23 publications

References 17 publications

Path Avoidance System of Intelligent Robot Based on Computer Vision

Path Avoidance System of Intelligent Robot Based on Computer Vision

Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

Trajectory Generation of a Quadrotor Transporting a Bulky Payload in the Cluttered Environments

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