A study on path planning for small mobile robot to move in forest area

Tanaka, Katsuaki; Okamoto, Y.; Ishii, Hiroyuki; Kuroiwa, Daisuke; Yokoyama, Hiroya; Inoue, Shintaro; Shi, Qing; Okabayashi, Satoshi; Sugahara, Yusuke; Takanishi, Atsuo

doi:10.1109/robio.2017.8324740

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…[Hellström et al, 2008] discusses different planning algorithms (A*, elastic bands, potential fields) for forwarder machines; however, no results are shown since it is a pre-study only. More examples of forest navigation using graph search algorithms to compute paths can be found in [Tanaka et al, 2017;Mowshowitz et al, 2018]. Compared to the Unmanned Ground Vehicles (UGVs), much more work has been done for Unmanned Aerial Vehicle (UAV) path planning in forests, and examples can be found in, e.g., [Cui et al, 2014;Liao et al, 2016;Pizetta et al, 2018].…”

Section: Related Workmentioning

confidence: 99%

Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester

Jelavić¹,

Jud²,

Egli³

et al. 2022

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This paper presents a system for autonomously conducting precision harvesting missions using a legged harvester. Precision tree harvesting removes some trees selectively, while leaving neighboring trees intact. Our robot performs the challenging task of navigation and tree grabbing in a confined, GPS-denied forest environment. We propose strategies for mapping, localization, planning, and control and integrate them into a fully autonomous system. The mission starts with a human mapping the area of interest using a detachable, custom sensor module. Subsequently, a human expert selects the specific trees for harvesting. The sensor module is then mounted on the machine and used for localization within the created map. A planning algorithm searches for both an approach-pose and a path in a single path planning problem. We design a path-following controller exploiting the legged harvester’s capabilities for negotiating rough terrain. Upon reaching the approach-pose, the machine grabs a tree with a general-purpose gripper. Our system has been tested in both emulated and natural forest settings. To the best of our knowledge, ours is the first robot to demonstrate such a level of autonomy on a full-size, hydraulic machine operating in a realistic environment.

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Section: Related Workmentioning

confidence: 99%

Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester

Jelavić¹,

Jud²,

Egli³

et al. 2022

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“…Simultaneous location and mapping problem and (Hutangkabodee et al, 2005) that uses the binary thresholding segmentation technique to orient and locate the UAV. Another sector is agriculture, in which (Pierzchała et al, 2018) uses a system of sensors integrated into a UAV with the aim of measuring humidity and temperature in a greenhouse; militia (Tanaka et al, 2017), where it implements an automation kit in a military vehicle to fulfill surveillance and navigation missions by teleoperation. In the forestry sector (Alberts et al, 2008) developed a UAV that works together with an UAV for fire detection in forest areas.…”

Section: Introductionmentioning

confidence: 99%

Computer vision for unmanned aerial vehicles in agriculture: applications, challenges, and opportunities

et al. 2023

The Scientific Temper

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Unmanned Aerial Vehicles (UAVs), commonly called drones, have gained significant attention in agriculture due to their potential to revolutionize traditional farming practices. This paper explores the integration of computer vision techniques with UAV technology to enhance agricultural processes. The fusion of these two domains has the potential to provide farmers and agronomists with valuable insights for optimized decision-making. The primary focus of this research is to showcase the various applications of computer vision for UAVs in agriculture. The paper begins by presenting an overview of the challenges faced by modern agriculture, such as resource optimization, crop monitoring, disease detection, and yield prediction. It then delves into the technological advancements in UAVs and their suitability for addressing these challenges.

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Control of an omnidirectional mobile robot with wheels connected by passive sliding joints

Terakawa

Komori

Fujimoto

2019

JAMDSM

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To solve problems of conventional mobile robots, such as constrained mobility due to nonholonomic wheels or complicated structure due to specialized wheels, we propose a novel omnidirectional mobile robot named slidable-wheeled omnidirectional mobile robot (SWOM). SWOM has three conventional wheels connected to the main body by passive sliding joints, which enable the main body to make omnidirectional movement in spite of the nonholonomic constraints on the wheels. Thus, SWOM achieves both superb mobility and simple structure. However, its behavior is described as a nonlinear system with nonholonomic constraints, which has difficulty with control because this type of system does not have a general design method for a stabilizing controller. This study aims to develop a controller for SWOM using state feedback linearization. This paper presents the following achievements: An exactly linearized state equation is derived using feedback and coordinate transformation based on the kinematics of SWOM. The unwanted singular configurations of the system are discussed and a control strategy to avoid them is proposed. Then, a stabilizing controller that enables SWOM to reach a designated position and orientation is designed. Through a numerical simulation and an experiment using a SWOM prototype, the effectiveness of the developed control system was verified.

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A study on path planning for small mobile robot to move in forest area

Cited by 4 publications

References 12 publications

Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester

Robotic Precision Harvesting: Mapping, Localization, Planning and Control for a Legged Tree Harvester

Computer vision for unmanned aerial vehicles in agriculture: applications, challenges, and opportunities

Control of an omnidirectional mobile robot with wheels connected by passive sliding joints

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