A Teleoperation Framework for Mobile Robots Based on Shared Control

Luo, Jing; Lin, Zhidong; Li, Yanan; Yang, Chenguang

doi:10.1109/lra.2019.2959442

Cited by 122 publications

(50 citation statements)

References 33 publications

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“…In this paper, the OMR structure is shown in the Figure 3. It is composed of four Mecanum wheels whose rotational axis is at a 45-degree angle to the robot body, and each pair of diagonal wheels has the same direction [34]. This design allows the mobile robot to move in all directions.…”

Section: Kinematics Of the Omnidirectional Mobile Robotmentioning

confidence: 99%

BIM Fork: Are Smart Contracts in Construction More Likely to Prosper with or without BIM?

Mason

2019

J. Leg. Aff. Dispute Resolut. Eng. Constr.

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This paper proposes a novel control system for the path planning of an omnidirectional mobile robot based on mixed reality. Most research on mobile robots is carried out in a completely real environment or a completely virtual environment. However, a real environment containing virtual objects has important actual applications. The proposed system can control the movement of the mobile robot in the real environment, as well as the interaction between the mobile robot's motion and virtual objects which can be added to a real environment. First, an interactive interface is presented in the mixed reality device HoloLens. The interface can display the map, path, control command, and other information related to the mobile robot, and it can add virtual objects to the real map to realize a real-time interaction between the mobile robot and the virtual objects. Then, the original path planning algorithm, vector field histogram* (VFH*), is modified in the aspects of the threshold, candidate direction selection, and cost function, to make it more suitable for the scene with virtual objects, reduce the number of calculations required, and improve the security. Experimental results demonstrated that this proposed method can generate the motion path of the mobile robot according to the specific requirements of the operator, and achieve a good obstacle avoidance performance.

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Section: Kinematics Of the Omnidirectional Mobile Robotmentioning

confidence: 99%

BIM Fork: Are Smart Contracts in Construction More Likely to Prosper with or without BIM?

Mason

2019

J. Leg. Aff. Dispute Resolut. Eng. Constr.

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“…Reference [7] proposed a model-predictive controller with input and output state constraints included. To improve the obstacle avoidance performance of a remotely controlled OWMR, reference [8] suggested the EMG (electromyography) and artificial potential field hybrid controller.…”

Section: Introductionmentioning

confidence: 99%

Development of a Hybrid Path Planning Algorithm and a Bio-Inspired Control for an Omni-Wheel Mobile Robot

Kim

Suh

Han

2020

Sensors

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This research presents a control structure for an omni-wheel mobile robot (OWMR). The control structure includes the path planning module and the motion control module. In order to secure the robustness and fast control performance required in the operating environment of OWMR, a bio-inspired control method, brain limbic system (BLS)-based control, was applied. Based on the derived OWMR kinematic model, a motion controller was designed. Additionally, an optimal path planning module is suggested by combining the advantages of A* algorithm and the fuzzy analytic hierarchy process (FAHP). In order to verify the performance of the proposed motion control strategy and path planning algorithm, numerical simulations were conducted. Through a point-to-point movement task, circular path tracking task, and randomly moving target tracking task, it was confirmed that the suggesting motion controller is superior to the existing controllers, such as PID. In addition, A*–FAHP was applied to the OWMR to verify the performance of the proposed path planning algorithm, and it was simulated based on the static warehouse environment, dynamic warehouse environment, and autonomous ballet parking scenarios. The simulation results demonstrated that the proposed algorithm generates the optimal path in a short time without collision with stop and moving obstacles.

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“…With the rapid development of sensor technologies, control technologies, and computer technologies, the application of teleoperated robots has mainly been concentrated on several operation modes, i.e. direct manipulation [12,13], supervised manipulation [14,15], and shared control [16][17][18]. For direct manipulation, remote robots follow the human operator's motion like a puppet without autonomous abilities.…”

Section: Introductionmentioning

confidence: 99%

Combined perception, control, and learning for teleoperation: key technologies, applications, and challenges

Luo

Yang

2020

Cognitive Computation and Systems

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Teleoperation provides a promising way for human-robot collaboration in the unknown or unstructured environments to perform a cooperative task. It enables humans to complete a task at a remote side and combines both the human's intelligence and the robots' capabilities in a collaborative task. Therefore, it is necessary to conduct cross researches in terms of robotics, artificial intelligence, sensors, and mechatronics. This study covers the state-of-the-arts research in terms of perception, control, and learning. In this review, key technologies about information perception mechanism, control algorithms, human-robot interface, and robot learning strategies for teleoperation are introduced. Then, a comprehensive survey is summarised in representative applications in teleoperation, and the existing challenges and potential directions of the development are discussed.

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A Teleoperation Framework for Mobile Robots Based on Shared Control

Abstract: 2020) A teleoperation framework for mobile robots based on shared control. IEEE Robotics and Automation Letters, 5 (2).

Cited by 122 publications

References 33 publications

BIM Fork: Are Smart Contracts in Construction More Likely to Prosper with or without BIM?

BIM Fork: Are Smart Contracts in Construction More Likely to Prosper with or without BIM?

Development of a Hybrid Path Planning Algorithm and a Bio-Inspired Control for an Omni-Wheel Mobile Robot

Combined perception, control, and learning for teleoperation: key technologies, applications, and challenges

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