Investigation of the tip-over condition and motion strategy for a tracked vehicle with sub-tracks climbing over an obstacle on a slope

Yajima, Ryosuke; Nagatani, Keiji

doi:10.1109/ssrr.2018.8468638

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…The second type is the geometry‐based method. They perform force analysis and pose prediction for the contact process between a tracked robot and a specific terrain (Howard et al, 2014), containing single steps (Wang et al, 2007), stairs (Endo et al, 2016; Nagatani & Endo, 2016), and cylinders (Yajima & Nagatani, 2018; Yajima et al, 2019). Among them, Yuan et al (2019, 2020) divided the process of crossing a single step into multiple stages, where each stage was modeled, and the control law was designed based on geometric relationships.…”

Section: Related Workmentioning

confidence: 99%

“…to increase the level of autonomy of articulated tracked robots, including (i) estimating robot chassis pose as control target (Gianni et al, 2016;Okada et al, 2011), (ii) modeling specific terrain structures and designing simple control laws based on kinematic and dynamic analysis (Yajima & Nagatani, 2018;Yajima et al, 2019), and (iii) using machine learning methods to estimate flipper motions with terrain and robot pose as inputs (Pecka et al, 2018). Among these works, estimating the robot poses plays a core role, especially in predicting the poses in unreached places.…”

Section: Imitating Human Operations Several Research Efforts Have Bee...mentioning

confidence: 99%

“…The experienced human operator can control the flipper motion based on the robot's current pose and the upcoming terrain to ensure the robot can pass through smoothly. Imitating human operations, several research efforts have been made to increase the level of autonomy of articulated tracked robots, including (i) estimating robot chassis pose as control target (Gianni et al, 2016; Okada et al, 2011), (ii) modeling specific terrain structures and designing simple control laws based on kinematic and dynamic analysis (Yajima & Nagatani, 2018; Yajima et al, 2019), and (iii) using machine learning methods to estimate flipper motions with terrain and robot pose as inputs (Pecka et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Geometry‐based flipper motion planning for articulated tracked robots traversing rough terrain in real‐time

Chen,

Huang,

Pan

et al. 2023

Journal of Field Robotics

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Tracked robots operating on rough terrain are often equipped with controllable flippers to help themselves overcome large obstacles or gaps. How to automate the control of these auxiliary flippers to achieve autonomous traversal remains an open question, which still necessitates inefficient manual teleoperation in practice. To tackle this problem, this article presents a geometry‐based motion planning method for an articulated tracked robot to self‐control its flippers during autonomous or semiautonomous traversal over rough terrain in urban search and rescue environments. The proposed method is developed by combining dynamic programming with a novel geometry‐based pose prediction method of high computational efficiency, which is applicable for typical challenging rescue terrains, such as stairs, Stepfields, and rails. The efficient pose prediction method allows us to make thousands of predictions about the robot poses at future locations for given flipper configurations within the onboard sensor range. On the basis of such predictions, our method evaluates the entire discretized configuration space and thereby determines the optimal flipper motion online for a smooth traversal over the terrain. The overall planning algorithm is tested with both simulated and real‐world robots and compared with a reinforcement‐learning‐based method using the RoboCup Rescue Robot League standard testing scenarios. The experimental results show that our method enables the robots to automatically control the flippers, successfully go over challenging terrains, and outperform the baseline method in passing smoothness and robustness to different terrains.

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