Fast Obstacle Avoidance Based on Real-Time Sensing

Article Robotics

Mobile Robot Navigation Functions Tuned by Sensor Readings in Partially Known Environments

Savvas G. Loizou et al.

Summary: This letter extends the theory of mobile robot navigation functions to planar environments populated by unknown obstacles. It introduces on-line tuning of navigation functions based on sensor readings and the robot state. The feedback control law ensures smooth and monotonic approach to the target.

IEEE ROBOTICS AND AUTOMATION LETTERS (2022)

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Article Robotics

Avoiding Dense and Dynamic Obstacles in Enclosed Spaces: Application to Moving in Crowds

Lukas Huber et al.

Summary: This article presents a closed-form approach to constrain the flow within a given volume and around objects, ensuring it converges to a fixed point. The technique allows a robot to navigate in enclosed corridors while avoiding static and moving obstacles. It has been tested in dense crowd simulations and real outdoor environments, demonstrating successful traversal in the presence of diverse crowd patterns.

IEEE TRANSACTIONS ON ROBOTICS (2022)

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Article Robotics

Reactive Navigation in Crowds for Non-Holonomic Robots With Convex Bounding Shape

David J. Gonon et al.

Summary: This method is designed for non-holonomic robots of convex shape to avoid collisions with moving obstacles in crowds. Experimental results show that the method successfully avoids collisions with pedestrians in autonomous driving mode by simulating real crowd movements.

IEEE ROBOTICS AND AUTOMATION LETTERS (2021)

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Article Robotics

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Mikhail Koptev et al.

Summary: This letter introduces a real-time self-collision avoidance approach for whole-body humanoid robot control, which generates collision-free motions by learning boundary functions and employs machine learning techniques to improve computational efficiency and accuracy.

IEEE ROBOTICS AND AUTOMATION LETTERS (2021)

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Article Automation & Control Systems

Control Barrier Function-Based Quadratic Programs Introduce Undesirable Asymptotically Stable Equilibria

Matheus F. Reis et al.

Summary: Control Lyapunov functions (CLFs) and control barrier functions (CBFs) have been used to develop provably safe controllers by means of quadratic programs (QPs). However, the framework can introduce equilibrium points, particularly at the boundary of the safe set, into the closed-loop system. Explicit conditions are derived to ensure stability of these undesired equilibria, providing a solution to avoid them in the design of collision-free controllers.

IEEE CONTROL SYSTEMS LETTERS (2021)

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Article Robotics