• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.4
• /
• pp.617-628
• /
• 2022

Ascon is one of the final round candidates of the NIST lightweight cryptography contest, which has been underway since 2015, and supports hash modes Ascon-Hash and Ascon-Xof. In this paper, we develop a MILP model for collision attack on the Ascon-Hash and search for a differential trail that can be used in a quantum setting through the model. In addition, we present an algorithm that allows an attacker who can use a quantum computer to find a quantum free-start collision attack of 3-round Ascon-Hash using the discovered differential trail. This attack is meaningful in that it is the first to analyze a collision attack on Ascon-Hash in a quantum setting.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.423-427
• /
• 1993

A velocity planning method is proposed that ensures collision-free and minimal delay-time motions for two robotic manipulators and auxiliary equipments. Additional path, which makes robot start with possible largest speed, is added to the original prescribed path of one of two robots, and this running start along the additional path reduces delay time introduced to avoid collision between the robots and therefore reduces total traveling time.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.896-899
• /
• 1996

A new algorithm for planning a collision free path is developed based on linear parametric curve. A collision-free path is viewed as a connected space curve in which the path consists of two straight curve connecting start to target point. A single intermediate connection point is considered in this paper and is used to manipulate the shape of path by organizing the control point in polar coordinate (.theta.,.rho.). The algorithm checks interference with obstacles, defined as GM (Geometry Mapping), and maps obstacles in Euclidean Space into images in CPS (Connection Point Space). The GM for all obstacles produces overlapping images of obstacle in CPS. The clear area of CPS that is not occupied by obstacle images represents collision-free paths in Euclidean Space. Any points from the clear area of CPS is a candidate for a collision-free path. A simulation of GM for number of cases are carried out and results are presented including mapped images of GM and performances of algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.12
• /
• pp.1992-2007
• /
• 1997

A new algorithm for planning a collision-free path is developed based on linear prametric curve. In this paper robot is assumed to a point, and two linear parametric curve is used to construct a path connecting start and goal point, in which single intermediate connection point between start and goal point is considered. The intermediate connection point is set in polar coordinate(${\theta}{\delta}$) , and the interference between path and obstacle is mapped into CPS(connection point space), which is defined a CWS GM(circular work space geometry mapping). GM of all obstacles in workspace creates overlapping images of obstacle in CPS(Connection Point Space). The GM for all obstacles produces overlapping images of obstacle in CPS. The empty area of CPS that is not occupied by obstacle images represents collision-free paths in Euclidian Space. A GM based on connection point in elliptic coordinate(${\theta}{\delta}$) is also developed in that the total length of path is depend only on the variable .delta.. Hence in EWS GM(elliptic work space geometry mapping), increasing .delta. and finding the value of .delta. for collision-free path, the shortest path can be searched without carring out whole GM. The GM of obstacles expersses all possible collision-free path as empty spaces in CPS. If there is no empty space available in CPS, it indicates that path planning is not possible with given number of connection points, i.e. path planning is failed, and it is necessary to increase the number of connection point. A general case collision-free path planning is possible by appling GM to configuration space obstacles. Simulation of GM of obstacles in Euclidian space is carried out to measure performance of algorithm and the resulting obstacle images are reported.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.4
• /
• pp.362-367
• /
• 2011

The collision-free path of a manipulator should be regenerated in the real time to achieve collision safety when obstacles or humans come into the workspace of the manipulator. A probabilistic roadmap (PRM) method, one of the popular path planning schemes for a manipulator, can find a collision-free path by connecting the start and goal poses through the roadmap constructed by drawing random nodes in the free configuration space. The path planning method based on the configuration space shows robust performance for static environments which can be converted into the off-line processing. However, since this method spends considerable time on converting dynamic obstacles into the configuration space, it is not appropriate for real-time generation of a collision-free path. On the other hand, the method based on the workspace can provide fast response even for dynamic environments because it does not need the conversion into the configuration space. In this paper, we propose an efficient real-time path planning by combining the PRM and the potential field methods to cope with static and dynamic environments. The PRM can generate a collision-free path and the potential field method can determine the configuration of the manipulator. A series of experiments show that the proposed path planning method can provide robust performance for various obstacles.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1128-1131
• /
• 1996

The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.2 no.6
• /
• pp.57-65
• /
• 1994

A collision-free path planning algorithm between an articulated robot and polyhedral obstacles using configuration space is presented. In configuration space, a robot is treated as a point and obstacles are treated as grown forbidden regions. Hence path planning problem is transformed into moving a point from start position to goal position without entering forbidden regions. For mapping to 3D joint space, slice projection method is used for first revolute joint and inverse kinematics is used for second and third revolute joint considering kinematic characteristics of industrial robot. Also, three projected 2D joint spaces are used in search of collision-free path. A proper example is provided to illustrate the proposed algorithm.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.1
• /
• pp.107-117
• /
• 2004

A new algorithm for planning a collision-free path based on an algebraic curve as well as the concept of path space is developed. Robot path planning has so far been concerned with generating a single collision-free path connecting two specified points in a given robot workspace with appropriate constraints. In this paper, a novel concept of path space (PS) is introduced. A PS is a set of points that represent a connection between two points in Euclidean metric space. A geometry mapping (GM) for the systematic construction of path space is also developed. A GM based on the 2$^{nd}$ order base curve, specifically Bezier curve of order two is investigated for the construction of PS and for collision-free path planning. The Bezier curve of order two consists of three vertices that are the start, S, the goal, G, and the middle vertex. The middle vertex is used to control the shape of the curve, and the origin of the local coordinate (p, $\theta$) is set at the centre of S and G. The extreme locus of the base curve should cover the entire area of actual workspace (AWS). The area defined by the extreme locus of the path is defined as quadratic workspace (QWS). The interference of the path with obstacles creates images in the PS. The clear areas of the PS that are not mapped by obstacle images identify collision-free paths. Hence, the PS approach converts path planning in Euclidean space into a point selection problem in path space. This also makes it possible to impose additional constraints such as determining the shortest path or the safest path in the search of the collision-free path. The QWS GM algorithm is implemented on various computer systems. Simulations are carried out to measure performance of the algorithm and show the execution time in the range of 0.0008 ~ 0.0014 sec.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.6
• /
• pp.674-680
• /
• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.53.2-53
• /
• 2001

The Non-Contact Optical Sensor using the Hologram Laser for CD Pickup was developed to measure a shape of transparent objects and shown a good performance. Therefore the problems caused by the contact sensor are solved by using the Non-Contact Sensor. The Non-Contact Sensor has to move toward the objects and obtain the Focus Error Signal to measure a position of transparent objects. However, if the distance between the sensor and the object is shorter than the working distance of the objective lens, the sensor will be collided against the objects. In this paper we proposed a new algorithm to estimate the start position of the Focus Error Signal to solve the problems of collision between the sensor and the objects. In addition, we verified that the algorithm is free from the collision in the real time measurement.