Journal ArticleDOI
Extending Collision Avoidance Methods to Consider the Vehicle Shape, Kinematics, and Dynamics of a Mobile Robot
Javier Minguez,Luis Montano +1 more
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TLDR
This paper is a methodology to consider the exact shape and kinematics, as well as the effects of dynamics in the collision avoidance layer, since the original avoidance method does not address them.Abstract:
Most collision avoidance methods do not consider the vehicle shape and its kinematic and dynamic constraints, assuming the robot to be point-like and omnidirectional with no acceleration constraints. The contribution of this paper is a methodology to consider the exact shape and kinematics, as well as the effects of dynamics in the collision avoidance layer, since the original avoidance method does not address them. This is achievable by abstracting the constraints from the avoidance methods in such a way that when the method is applied, the constraints already have been considered. This study is a starting point to extend the domain of applicability to a wide range of collision avoidance methods.read more
Citations
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Journal ArticleDOI
Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey
TL;DR: Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are reviewed, and particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.
Journal ArticleDOI
Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges
TL;DR: The aim of this paper is to succinctly summarize and review the path smoothing techniques in robot navigation and discuss the challenges and future trends.
Posted Content
Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control.
TL;DR: This work uses Flow to develop reliable controllers for complex problems, such as controlling mixed-autonomy traffic (involving both autonomous and human-driven vehicles) in a ring road, and shows that even simple neural network policies can solve the stabilization task across density settings and generalize to out-of-distribution settings.
Smooth and Efficient Obstacle Avoidance for a Tour Guide Robot
TL;DR: In this article, the authors present the local path planning and obstacle avoidance method used on the autonomous tour-guide robot RoboX, which has proven its value during a 5 month operation of ten such robots in a real-world application, a very crowded exhibition.
Journal ArticleDOI
A Telepresence Mobile Robot Controlled With a Noninvasive Brain–Computer Interface
TL;DR: The overall result was that all participants were able to complete the designed tasks, reporting no failures, which shows the robustness of the system and its feasibility to solve tasks in real settings where joint navigation and visual exploration were needed.
References
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Journal ArticleDOI
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Book
Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Book
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Book
An Behavior-based Robotics
TL;DR: Following a discussion of the relevant biological and psychological models of behavior, the author covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence.
Journal ArticleDOI
The dynamic window approach to collision avoidance
TL;DR: This approach, designed for mobile robots equipped with synchro-drives, is derived directly from the motion dynamics of the robot and safely controlled the mobile robot RHINO in populated and dynamic environments.
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