Obstacle avoidance

Résumé

In robotics, obstacle avoidance is the task of satisfying some control objective subject to non-intersection or non-collision position constraints. What is critical about obstacle avoidance concept in this area is the growing need of usage of unmanned aerial vehicles in urban areas for especially military applications where it can be very useful in city wars. Normally obstacle avoidance is considered to be distinct from path planning in that one is usually implemented as a reactive control law while the other involves the pre-computation of an obstacle-free path which a controller will then guide a robot along. With recent advanced in the autonomous vehicles sector, a good and dependable obstacle avoidance feature of a driverless platform is also required to have a robust obstacle detection module. Reactive obstacle avoidance is a behavior based control strategy in a robot. It is a task similar to the navigation problem and produces a collision free motion. See also

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Source officielle

https://en.wikipedia.org/wiki/Obstacle_avoidance

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Unités associées (9)

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Cours associés (1)

The course teaches the basics of autonomous mobile robots. Both hardware (energy, locomotion, sensors) and software (signal processing, control, localization, trajectory planning, high-level control) will be tackled. The students will apply the knowledge to program and control a real mobile robot.

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Avoidance of Convex and Concave Obstacles with Convergence ensured through Contraction

Aude Billard, Lukas Huber

This paper presents a closed-form approach to obstacle avoidance for multiple moving convex and star-shaped concave obstacles. The method takes inspiration in harmonic-potential fields. It inherits the convergence properties of harmonic potentials. We prove impenetrability of the obstacle’s hull and asymptotic stability at a final goal location, using contraction theory. We validate the approach in a simulated co-worker industrial environment, with one KUKA arm engaged in a pick and place grocery task, avoiding in real-time humans moving in its vicinity and in simulation to drive wheel-chair robot in the presence of moving obstacles.

2019

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Unfreezing Social Navigation: Dynamical Systems based Compliance for Contact Control in Robot Navigation

Aude Billard, Vaibhav Gupta, Diego Felipe Paez Granados

Large efforts have focused on ensuring that the controllers for mobile service robots follow proxemics and other social rules to ensure both safe and socially acceptable distance to pedestrians. Nonetheless, involuntary contact may be unavoidable when the robot travels in crowded areas or when encountering adversarial pedestrians. Freezing the robot in response to contact might be detrimental to bystanders' safety and prevents it from achieving its task. Unavoidable contacts must hence be controlled to ensure the safe and smooth travelling of robots in pedestrian alleys. We present a force-limited and obstacle avoidance controller integrated into a time-invariant dynamical system (DS) in a closed-loop force controller that let the robot react instantaneously to contact or to the sudden appearance of pedestrians. Mitigating the risk of collision is done by modulating the velocity commands upon detecting a contact and by absorbing part of the contact force through active compliant control when the robot bumps inadvertently against a pedestrian. We evaluated our method with a personal mobility robot -Qolo- showing contact mitigation with passive and active compliance. We showed the robot able to overcome an adversarial pedestrian within 9 N of the set limit contact force for speeds under 1 m/s. Moreover, we evaluated integrated obstacle avoidance proving the ability to advance without incurring any other collision.

IEEE2022

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This paper proposed a fuzzy controller for the autonomous navigation problem of robotic systems in a dynamic and uncertain environment. In particular, we are interested in determining the robot motion to reach the target while ensuring their own safety and that of different agents that surround it. To achieve these goals, we have adopted a fuzzy controller for navigation and avoidance obstacle, taking into account the changing nature of the environment. The approach has been tested and validated on a Thymio II robots set. As application field, we have chosen a parking problem.

2014

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