Jongwoo Park's research while affiliated with Korea Institute of Machinery and Materials and other places

... Given that a flexible body operates passively, it exhibits high shape adaptability with fewer actuators and simple control techniques. In particular, soft grippers demonstrated a high adaptability based on compliant materials and mechanisms [18]- [21]. Rigid grippers require accurate information regarding the shape and location of things, in addition to the strategies for holding things. ...

... These vehicles are fitted with modern sensors (Pingzeng et al. 2011), cameras, and robotic arms to precisely identify, pick, and collect ripe crops. Unmanned harvesters can be configured to perform effectively (Choi et al. 2022) and correctly, boosting harvesting pace and reducing the need for manual labor. They are particularly useful for crops that require careful handling, such as fruits and vegetables (Hua et al. 2019;Zhang et al. 2022). ...

... Another area of investigation is force control, covering contact force and self-weight compensation [15]- [17]. Researchers have designed specialized joint modules [18], [19] and dynamic algorithms to drive robot arms with active compensation torque. Some designs position motors at the base of the arm to prevent an increase in the robot arm's inertia, with power transmission achieved through wires and tubes. ...

... Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. in soft robotic actuators, tactile sensors, materials, visual and haptic perception, and machine learning have enabled significant progress toward dexterous human-like robotic grasping [1][2][3]. Development of soft robots has opened up new possibilities for grasping and functional tasks due to their inherent material and structural compliance properties [4][5][6]. Despite the recent progress, most of the soft robotic manipulators and grippers are limited to performing dedicated operational tasks. ...

... Last but not least, there are many applications and proposals to improve parameter estimations in the applications for some specific research fields. Some studies are; improving parameter estimations in network services, quality of services and digital signal processing via machine learning classification [32], improving parameter estimations in Photovoltaic models via dynamic switch probability [33], improving parameter estimation for lithium batteries models via neural network [34], improving parameter estimation for lithium batteries models with comparing methods to gain better method [35], improving generalized and group-generalized parameter estimations for multi-criteria decision-making via Pythagorean fuzzy set [36], improving electrical power system stability via power system stabilizer parameter estimation [37], improving parameter estimation for the robot manipulators via a separation technique [38], improving parameter estimation for the 3D scanner models via plane fitting [39], improving parameter estimation for inductive power transfer system via load voltage estimation [40], improving parameter estimation for power system parameters via a rapid estimation algorithm [41] and improving parameter estimation for epidemic models via likelihood functions and Kalman filtering [42]. ...

... Soft robotic grippers have been actively employed in the past decade, rapidly replacing rigid links in various applications, including industrial (Fontanelli et al., 2020), medical (Jang et al., 2021;Rateni et al., 2015), and agricultural (Blanes et al., 2015;Lee et al., 2020a;Low et al., 2021;Navas et al., 2021) applications. Because these applications deal with delicate or irregular objects, the traditional approach of using a robotic hand with multiple rigid fingers that mimic a human hand (Lange et al., 2021;Rahman et al., 2018) is no longer the most effective. ...

... This is due to several reasons. First, commercial force/torque (F/T) sensors are often too bulky and expensive for smaller-sized humanoid robots [3,4,5] and many existing customized miniature F/T sensors require complex manufacturing and calibration processes [6,7,8,9]. Second, common smaller-sized humanoids possess underpowered motors, leading to imprecise kinematic control of the robot's end-effectors [10]. Therefore, the object can easily slip out of the grip during the manipulation process. ...

... With highly mechanized and automated manufacturing workshops of today, although modern equipment can complete the majority of manual operations, numerous repetitive and high-precision manual assembly operations, persist, including precision assembly of armature parts [1] and precision parts assembly with small tolerance range [2]. While the automated machinery requires operators to maintain high attention and invest significant cognitive resources; it also requires them to possess better finger control ability to ensure precise pickup, movement, and manipulation of objects from a place [3,4], thereby resulting in a significant upsurge in the mental and physical load of operators during the task. ...

... The welding system is mainly composed of welding machine tool system, welding power supply system, welding auxiliary system, and integrated control system. [14][15][16][17][18] The welding machine tool includes bed, positioner, tooling fixture, operator, and so on, and the welding auxiliary system includes welding torch swinger, arc voltage controller, and so on. Integrated control system includes electrical control cabinet, touch screen, operation panel, control cable and trunking, and so on. ...