• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.650-657
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• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.299-307
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• 2023

In the midst of accelerating wars around the world, unmanned robot technology that can guarantee the safety of human life is emerging. ERP-42 is a modular platform that can be used according to the application. In the field of defense, it can be used for transporting supplies, reconnaissance and surveillance, and medical evacuation in conflict areas. Due to the nature of the military environment, atypical environments are predominant, and in such environments, the platform's path followability is an important part of mission performance. This paper focuses on reducing the minimum turning radius in terms of improving path followability. The minimum turning radius of the existing 2WS/2WD in-wheel platform was reduced by increasing the torque of the independent driving in-wheel motor on the rear wheel to generate oversteer. To determine the degree of oversteer, two GPS were attached to the center of the front and rear wheelbases and measured. A closed-loop speed control method was used to maintain a constant rotational speed of each wheel despite changes in load or torque.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.499-506
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• 2019

An intelligent robot should decide its behavior accordingly to the dynamic changes in the environment and user's requirements by evaluating options to choose the best one for the current situation. Many intelligent robot systems that use the Procedural Reasoning System (PRS) accomplishes such task management functions by defining the priority functions in the task model and evaluating the priority functions of the applicable tasks in the current situation. The priority functions, however, are defined locally inside of the plan, which exhibits limitation for the tasks for multi-domain services because global contexts for overall prioritization are hard to be expressed in the local priority functions. Furthermore, since the prioritization functions are not defined as an explicit module, reuse or extension of the them for general context is limited. In order to remove such limitations, we propose a policy-based meta-planning for general task management for multi-domain services, which provides the ability to explicitly define the utility of a task in the meta-planning process and thus the ability to evaluate task priorities for general context combining the modular priority functions. The ontological specification of the model also enhances the scalability of the policy model. In the experiments, adaptive behavior of a robot according to the policy model are confirmed by observing the appropriate tasks are selected in dynamic service environments.

• Journal of Biosystems Engineering
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• v.33 no.3
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• pp.186-195
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• 2008

In this paper, a prototype tele-operative system with a mobile base was developed in order to automate cultivation of house melon. A man-machine interactive hybrid decision-making system via tele-operative task interface was proposed to overcome limitations of computer image recognition. Identifying house melon including position data from the field image was critical to automate cultivation. And it was not simple especially when melon is covered partly by leaves and stems. The developed system was composed of 5 major modules: (a) main remote monitoring and task control module, (b) wireless remote image acquisition and data transmission module, (c) three-wheel mobile base mounted with a 4 dof articulated type robot manipulator (d) exchangeable modular type end tools, and (e) melon storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. A sequence of algorithms to identify location and size of a melon was performed based on the local image processing. Laboratory experiment showed the developed prototype system showed the practical feasibility of automating various cultivating tasks of house melon.