Kinematics analysis for obstacle-climbing performance of a rescue robot

Wang, Weidong; Du, Zhijiang; Sun, Lining

doi:10.1109/robio.2007.4522406

Cited by 10 publications

(6 citation statements)

References 5 publications

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“…When the height of the obstacle is known (obtained by the depth camera), the front and back swing arm angles and the robot pitch angle are obtained through the swing arm encoder and IMU sensor, and the stability margin angle can be obtained to carry out obstacle clearance planning based on the optimal stability margin. The detailed motion planning and stability analysis refer to our previous research (Wang et al, 2007).…”

Section: Search and Rescue Robot Systemmentioning

confidence: 99%

Development of a search and rescue robot system for the underground building environment

Wang

Ding

et al. 2023

Journal of Field Robotics

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The underground building environment plays an increasingly important role in the construction of modern cities. To deal with possible fires, collapses, and so on, in underground building space, it is a general trend to use rescue robots to replace humans. This paper proposes a dual-robot system solution for search and rescue in an underground building environment. To speed up rescue and search, the two robots focus on different tasks. However, the environmental perception information and location of them are shared. The primary robot is used to quickly explore the environment in a wide range, identify objects, cross difficult obstacles, and so on.The secondary robot is responsible for grabbing, carrying items, clearing obstacles, and so on. In response to the difficulty of rescue caused by unknown scenes, the Lidar, inertial measurement unit and multiview cameras are integrated for large-scale 3D environment mapping. The depth camera detects the objects to be rescued and locate them on the map. A six-degree-of-freedom manipulator with a two-finger gripper is equipped to open doors and clear roadblocks during the rescue. To solve the problem of severe signal attenuation caused by reinforced concrete walls, corners and long-distance transmission, a wireless multinode networking solution is adopted. In the case of a weak wireless signal, the primary robot uses autonomous exploration for environmental perception. Experimental results show the robots' system has high reliability in over-the-horizon maneuvering, teleoperation of the door opening and grasping, object searching, and environmental perception, and can be well applied to underground search and rescue.

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Section: Search and Rescue Robot Systemmentioning

confidence: 99%

Development of a search and rescue robot system for the underground building environment

Wang

Ding

et al. 2023

Journal of Field Robotics

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“…The UGV platform’s method of overcoming obstacles involves moving across space. The centroid must reach the location of the obstacle height to realize the obstacle surmounting [83, 84]. The centroid position has an impact on the obstacle-surmounting performance.…”

Section: Research Status Of Obstacle-surmounting Mechanism and Its Pe...mentioning

confidence: 99%

State of the art and future trends in obstacle-surmounting unmanned ground vehicle configuration and dynamics

Yue

Zheng

et al. 2023

Robotica

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This article presents a review of the platform configuration and dynamic of obstacle-surmounting unmanned ground vehicles (UGVs). For now, unmanned systems have emerged as a result of the rapid advancement of artificial intelligence and modern manufacturing techniques both domestically and internationally. The research on unmanned systems has been improved a lot. The UGV platform can execute transportation, recurring, and military tasks independently. For the high-level self-control, adaption, and maneuverability abilities, the UGV platform has been applied in the military, industry, and other special fields widely. The UGV platform usually performs tasks in an unstructured environment, so the all-terrain performance becomes a key factor restricting their operating efficiency and reliability. A brief literature review of the UGV platform is carried out in this article.

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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%

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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Kinematics analysis for obstacle-climbing performance of a rescue robot

Cited by 10 publications

References 5 publications

Development of a search and rescue robot system for the underground building environment

Development of a search and rescue robot system for the underground building environment

State of the art and future trends in obstacle-surmounting unmanned ground vehicle configuration and dynamics

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

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