Sharif Digital Repository

We study the problem of finding a target t from a start point s in street environments with the cooperation of two robots which have a minimal sensing capability; that is, robots do not know any information about the workspace including information on distances, edges, coordinates, angles etc. They just can detect the discontinuities in the visibility region of their location. The robots can detect target point t as soon as it enters their visibility region and have communication peripherals to send messages to each other. Our aim is to minimize the length of the path passed by the robots. We propose an online algorithm for robots such that they move in the workspace and find the target.... 

In this paper, we propose a new method for mobile robot path planning in dynamic environment when the trajectories of obstacles are unknown. Our algorithm first utilizes a global approach called clearance based probabilistic roadmap method to find a suitable path and then locally apply evolutionary algorithm to keep the structure of the path when obstacles collide with the path. As a result, the path will act like an elastic band. To reach real time applicability, a light fitness function is proposed compare to other genetic algorithms to reduce the computation time needed for calculating and repairing path. Simulation results show that our method not only can keep the original structure of... 

We give approximation algorithms and inapproximability results for a class of movement problems. In general, these problems involve planning the coordinated motion of a large collection of objects (representing anything from a robot swarm or firefighter team to map labels or network messages) to achieve a global property of the network while minimizing the maximum or average movement. In particular, we consider the goals of achieving connectivity (undirected and directed), achieving connectivity between a given pair of vertices, achieving independence (a dispersion problem), and achieving a perfect matching (with applications to multicasting). This general family of movement problems... 

The control of a brachiation robot has been the primary objective of this study. A brachiating robot is a type of a mobile arm that is capable of moving from branch to branch similar to a long-armed ape. In this paper, to minimize the actuator work, Pontryagin's minimum principle was used to obtain the optimal trajectories for two different problems. The first problem considers brachiation between fixed branches with different distance and height, whereas the second problem deals with the brachiating and catching of a moving target branch. Theoretical results show that the control effort in the proposed method is reduced by 25% in comparison with the target dynamics method which was proposed... 

This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimizethe... 

Cat free fall righting maneuverer has inspired many aerial, space and legged robotic research. Conservation of angular momentum principle is used to derive the inverse differential kinematic and TMT vector form dynamics of the motion for three robotic models: a two-link model, a three-link model with tail, and a comprehensive eight-link model with the addition of legs. The path planning problem in the presence of geometric and kinematic constraints is addressed using a novel singularity free single shooting optimization method. While a 2 DOF torso is sufficient to perform a full maneuver, the addition of the tail reduces the time and increases the maneuverability despite the leg motions that... 

In this paper, two online path planning methods are presented for SURENA III humanoid robot by using model predictive control scheme. The methods are general control schemes which can generate the online motions for walking of a humanoid robot. For lowering computational costs a three dimensional linear inverted pendulum model is used instead of the full dynamical model of the robot. The generated trajectories are then used for computing the zero-moment point (ZMP) of the robot and the joint torques. The resulted joint torques of the two methods are compared to torques obtained from Genetic Algorithm (GA) path planning method presented for SURENA III humanoid robot in previous studies. The... 

Using mobile robots in disaster areas can reduce risks and the search time in urban search and rescue operations. Optimal path-planning for mobile robotics can play a key role in the reduction of the search time for rescuing victims. In order to minimize the search time, the shortest path to the target should be determined. In this paper, a new integrated Reinforcement Learning—based method is proposed to search and find a hidden target in an unknown environment in the minimum time. The proposed algorithm is developed in two main phases. Depending on whether or not the mobile robot receives the signal from the hidden target, phases I or II of the proposed algorithm can be carried out. Then,... 

In this paper, a new method for path planning is proposed using a genetic algorithm (GA). Our method has two key advantages over existing GA methods. The first is a novel environment representation which allows a more efficient method for obstacles dilation in comparison to current cell based approaches that have a tradeoff between speed and accuracy. The second is the strategy we use to generate the initial population in order to speed up the convergence rate which is completely novel. Simulation results show that our method can find a near optimal path faster than computational geometry approaches and with more accuracy in smaller number of generations than GA methods. © 2009 IEEE  

This paper presents a new method for motion planning of mobile robots in dynamic environments based on wave expansion approach which avoids wave re-expansion in sudden obstacles case. Wave re-expansion in big scale environments takes considerable amount of time and process. A new wave expansion algorithm for path finding, either local minima or sudden obstacles are met, has been proposed, as socalled Impeditive Wall Following algorithm, that prevents reexpansion of wave. Furthermore, the simulation results reflects that how the work has improved the already-existing methods. By the use of Impeditive Wall following algorithm it's been tried to prevent the re-expansion of the wave. © 2009 IEEE... 

We give approximation algorithms and inapproximability results for a class of movement problems. In general, these problems involve planning the coordinated motion of a large collection of objects (representing anything from a robot swarm or firefighter team to map labels or network messages) to achieve a global property of the network while minimizing the maximum or average movement. In particular, we consider the goals of achieving connectivity (undirected and directed), achieving connectivity between a given pair of vertices, achieving independence (a dispersion problem), and achieving a perfect matching (with applications to multicasting). This general family of movement problems... 

Using mobile robots in disaster areas can reduce risks and the search time in urban search and rescue operations. Optimal path-planning for mobile robotics can play a key role in the reduction of the search time for rescuing victims. In order to minimize the search time, the shortest path to the target should be determined. In this paper, a new integrated Reinforcement Learning—based method is proposed to search and find a hidden target in an unknown environment in the minimum time. The proposed algorithm is developed in two main phases. Depending on whether or not the mobile robot receives the signal from the hidden target, phases I or II of the proposed algorithm can be carried out. Then,... 

Contact modeling plays a central role in motion planning, simulation and control of legged robots, as legged locomotion is realized through contact. The two prevailing approaches to model the contact consider rigid and compliant premise at interaction ports. Contrary to the dynamics model of legged systems with rigid contact (without impact) which is straightforward to develop, there is no consensus among researchers to employ a standard compliant contact model. Our main goal in this paper is to study the dynamics model structure of bipedal walking systems with rigid contact and a novel compliant contact model, and to present experimental validation of both models. For the model with rigid... 

In a multi-robot system, a number of autonomous robots would sense, communicate, and decide to move within a given domain to achieve a common goal. In the pursuit-evasion problem, a polygonal region is given and a robot called a pursuer tries to find some mobile targets called evaders. The goal of this problem is to design a motion strategy for the pursuer such that it can detect all the evaders. In this paper, we consider a new variant of the pursuit-evasion problem in which the robots (pursuers) each moves back and forth along an orthogonal line segment inside a simple orthogonal polygon P. We assume that P includes unpredictable, moving evaders that have bounded speed. We propose the... 

Lift path planning is a significant subtask in constructability analysis, sequencing, and scheduling of congested industrial modular projects, impacting project cost, and safety. Although intuitive lift planning is still prevalent among the practitioners, this manual process might be tedious and error-prone for hundreds of lifts. This research presents an automated lift path planning method for heavy crawler cranes in no-walk scenarios employing a robotics approach. This method treats the lifted object as a three-degree-of-freedom convex mobile robot with discretized rotational and continuous translational motions. The proposed resolution-complete method models the crane capacity chart,... 

This paper deals with control of the brachiation robot. The brachiation is a type of mobile robot that moves from branch to branch like a long-armed ape. Here, as a new innovation, Pontryagin's minimum principle is used to obtain the optimal trajectories for two different problems. The first problem is "Brachiation between fixed branches with different distance and height" and the second is "Brachiating and catching the moving target branch". Theoretical results show that the control effort in the proposed method is reduced by 25% in comparison with the "Target Dynamics" method which was proposed in prior articles for this robot. The obtained optimal trajectory also minimizes the brachiation... 

This study presents an online motion planning algorithm for generating reference trajectories during flight phases of a planar monopedal robot to transfer the configuration of the mechanical system from a specified initial pose to a specified final one. The algorithm developed in this research is based on the reachability and optimal control formulations of a time-varying linear system with input and state constraints. A two-level control scheme is developed for asymptotic stabilisation of a desired period-one orbit during running of the robot. Within-stride controllers, including stance and flight phase controllers, are employed at the first level. The flight phase controller is a feedback... 

This study presents a motion planning algorithm to generate a feasible periodic solution for a hybrid system describing running by a three-dimensional (3-D), three-link, three-actuator, monopedal robot. In order to obtain a symmetric running gait along a straight line, the hybrid system consists of two stance phases and two flight phases. The motion planning algorithm is developed on the basis of a finite-dimensional optimisation problem with equality and inequality constraints. By extending the concept of hybrid zero dynamics to running, the authors propose a time-invariant control scheme that is employed at two levels to locally exponentially stabilise the generated periodic solution for... 

This paper deals with the collision-free path planning of planar parallel robot by avoiding mechanical interferences and obstacle within the workspace. For this purpose, an Artificial Potential Field approach is developed. As the main contribution of this paper, In order to circumvent the local minima problem of the potential fields, a novel approach is proposed which is a combination of Potential Field approach, Fuzzy Logic and also a novel algorithm consisting of Following Obstacle as well as Virtual Obstacle methods, as a hybrid method. Moreover, the inverse kinematic problem of the 3-RRR parallel robot is analyzed and then the aforementioned hybrid method is applied to this mechanism in... 

In this study, a gait optimization routine is developed to generate walking patterns which demand the lowest friction forces for implementation. The aim of this research is to fully address the question “which walking pattern demands the lowest coefficient of friction amongst all feasible patterns?”. To this end, first, the kinematic structure of the considered 31 DOF (Degrees of Freedom) humanoid robot is investigated and a closed-form dynamics model for its lower-body is developed. Then, the medium through which the walking pattern generation is conducted is presented. In this medium, after designing trajectories for the feet and the pelvis, the joint space variables are obtained, using...