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This paper presents an approach of human-vehicle cooperative navigation system as an implementation of Advanced Driving Assistance Systems (ADAS). The driver-in-the-loop system contains commands by a human driver, which are verified and corrected by the interactive navigation algorithm based on Image-based Dynamic Window Approach (IDWA). Several autonomous driving components are involved including...
One of the key challenges in applying reinforcement learning to complex robotic control tasks is the need to gather large amounts of experience in order to find an effective policy for the task at hand. Model-based reinforcement learning can achieve good sample efficiency, but requires the ability to learn a model of the dynamics that is good enough to learn an effective policy. In this work, we develop...
Autonomous service mobile robots need to consistently, accurately, and robustly localize in human environments despite changes to such environments over time. Episodic non-Markov Localization addresses the challenge of localization in such changing environments by classifying observations as arising from Long-Term, Short-Term, or Dynamic Features. However, in order to do so, EnML relies on an estimate...
In this work, we consider the labeled multi-robot planning problem. In this paradigm, a team of robots at fixed start positions must navigate to pre-specified and noninterchangable goal positions. While many algorithms have been proposed for finding optimal solutions to this problem, most methods assume that the robots are kinematic agents, whereas in reality, robots often have high-order dynamics...
In this article we present a symbolic closed-form matrix formulation to obtain the dynamic equations of branched articulated multibody systems (AMS)s. The proposed approach uses geometric mechanics based on Screw Theory and Lie groups. Both Lagrange's and Newton-Euler's equation of motion are derived. Furthermore, the structure of the proposed set of geometric equations holds the intrinsic robot parameters...
This paper describes a fuzzy control methodology for continuous passive motion equipment (CPM). The methodology combines fields such as artificial intelligence, through the fuzzy controller development; and control engineering, joining an optimization mechanism of movement with closed loop control. Following UML-MARTE profile is used to modeling the methodology. Based on system input/output and a...
In this paper we are continuing in our research to show mutual intersection of two different areas of research: complex network and evolutionary computation. This research parer is focused on possibility to convert run of evolution algorithm to a complex network inspired by ants. Such network can then be analyzed to get useful information about algorithm dynamics. In this paper we focused on one global...
This paper describes a trajectory planning algorithm for mobile robot navigation in crowded environments; the aim is to solve the problem of planning a valid path through moving people.
Unmanned Aerial Vehicles are currently investigated as an important sub-domain of robotics, a fast growing and truly multidisciplinary research field. UAVs are increasingly deployed in real-world settings for missions in dangerous environments or in environments which are challenging to access. Combined with autonomous flying capabilities, many new possibilities, but also challenges, open up. To overcome...
In the paper new control algorithm for skid-steering mobile platforms has been presented. This control law is based on mathematical model of such object. In the model it has been assumed that wheels of the skid-steering platform are not coupled by tracks and that they can move without some slipping effects, namely with lack of longitudinal slipping of selected wheels and lack of lateral slipping of...
In order to solve the multi-robot task allocation problem in logistics warehouse environment, first a robot task allocation model is established in which a corresponding benefit function is established with a consideration of two mainly factors including time window and distance. Then the ant colony algorithm pheromone updating rule is improved combining with working environment and task allocation...
Many indoor navigation robots use structured light vision measurement systems (SLVMS) for mapping, localization, and obstacle avoidances. In these systems, the extraction of light stripe skeleton directly affects the accuracy of the final measurements. One of the problems in SLVMS is that when the light is projected to some rough surface it will cause strong diffuse reflection. Thus the light stripe...
This paper reviews recent developments extending sampling based motion planning algorithms to operate in dynamic environments. Sampling based planners provide an effective approach for solving high degree of freedom robot motion planning problems. The two most common algorithms are the Probabilistic Roadmap Method and Rapidly Exploring Random Trees. These standard techniques are well established,...
This paper proposes a novel algorithm, named dual multiobjective quantum-inspired evolutionary (DMQEA) algorithm augmented fuzzy cognitive map (FCM). DMQEA was developed to help users select preferable solutions out of the non-dominated ones and has been proven to be an effective way compared to other multi-objective optimization methods, such as MQEA, MQEA-PS, etc. DMQEA, in this paper, has been...
In this paper, an algorithm called transverse contracting dynamic system primitive (CDSP) to learn the dynamics of periodic motions from demonstrations is presented. Learning motion plans is essential in making robot programming possible by non-expert programmers as well as realizing human-robot collaboration. The complex periodic motion of the human arm is generated by an orbitally stable closed-loop...
This paper presents a detailed study to demonstrate the online tuning dynamic neural network PID controller to improve a joint angle position output performance of 4-joint robotic arm. The proposed controller uses a new updating weight rule model of the neural network architecture using multi-loop calculation of the fusion of the gradient algorithm with the cubature Kalman filter (CKF) which can optimize...
This paper presents a new path planning approach, in which the MAKLINK graph is constructed to describe the complex environment of the mobile robot, the enumeration method ideas into Dijkstra algorithm is used to obtain the shortest path, and the dynamic double mutation particle swarm optimization algorithm is adopted to get the optimal path. Finally, simulation results are used to illustrate the...
With the advancements in technology, robots has become systems that can learn and achieve complex behaviors in real life with the help of machine learning algorithms. Among those algorithms, reinforcement learning algorithms are widely used in robotics to teach the systems by trials and errors. In this work, our goal is to use the two different reinforcement algorithms, Q-learning and Adaptive Heuristic...
This paper proposes a new algorithm for solving the robot path planning problem which includes finding a path from a source to a destination subject to certain constraints. First, using the overhead view of the surroundings, a free space model is created using MAKLINK graph theory. Then Dijkstra's Algorithm is applied over the MAKLINK graph to obtain a sub-optimal path. This sub-optimal path is further...
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