Whole-Body Control With (Self) Collision Avoidance Using Vector Field Inequalities

This paper focuses on ground-moving target tracking of an unmanned aerial vehicle (UAV) in the presence of static obstacles and moving threat sources. Due to a UAV is restricted by airspace restrictions and measurement limitations during flight, we derive a dynamic path planning strategy by generating guidance vector filed combined Lyapunov vector field with collision avoidance potential function to track target in standoff distance loitering pattern, and resolved collision avoidance, simultaneously. This method relies only on the current information of the UAV and target, and generates a single-step route plan in realtime. Its performance is simple, efficient, and fast and have low computational complexity. The results of numerical simulation verify the effectiveness of the tracking and collision avoidance process of the UAV.

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Integrated Path Following and Collision Avoidance Using a Composite Vector Field

2019 IEEE 58th Conference on Decision and Control (CDC) ◽

10.1109/cdc40024.2019.9029203 ◽

2019 ◽

Author(s):

Weijia Yao ◽

Bohuan Lin ◽

Ming Cao

Keyword(s):

Vector Field ◽

Collision Avoidance ◽

Path Following

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On-Site Locomotion Planning for a Humanoid Robot with Stable Whole-Body Collision Avoidance Motion Guided by Footsteps and Centroidal Trajectory

International Journal of Humanoid Robotics ◽

10.1142/s021984361950035x ◽

2019 ◽

Vol 17 (01) ◽

pp. 1950035

Author(s):

Iori Kumagai ◽

Mitsuharu Morisawa ◽

Shin’ichiro Nakaoka ◽

Fumio Kanehiro

Keyword(s):

Motion Planning ◽

Collision Avoidance ◽

Dynamic Simulation ◽

Inverse Kinematics ◽

Humanoid Robot ◽

Computational Cost ◽

Body Motion ◽

Whole Body ◽

Planning Framework ◽

Narrow Space

In this paper, we propose a locomotion planning framework for a humanoid robot with stable whole-body collision avoidance motion, which enables the robot to traverse an unknown narrow space on the spot based on environmental measurements. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by utilizing global footstep planning results and its centroidal trajectory as a guide. In the global footstep planning phase, we modify the bounding box of the robot approximating the centroidal sway amplitude of the candidate footsteps. This enables the planner to obtain appropriate footsteps and transition time for next whole-body motion planning. Then, we execute sequential whole-body motion planning by prioritized inverse kinematics considering collision avoidance and maintaining its ZMP trajectory, which enables the robot to plan stable motion for each step in 223[Formula: see text]ms at worst. We evaluated the proposed framework by a humanoid robot HRP-5P in the dynamic simulation and the real world. The major contribution of our paper is solving the problem of increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive on-site locomotion planning in an unknown narrow space.

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Where Should I Look Optimised Gaze Control for Whole-Body Collision Avoidance in Dynamic Environments

IEEE Robotics and Automation Letters ◽

10.1109/lra.2021.3137545 ◽

2021 ◽

pp. 1-1

Author(s):

Mark Nicholas Finean ◽

Wolfgang Xaver Merkt ◽

Ioannis Havoutis

Keyword(s):

Collision Avoidance ◽

Dynamic Environments ◽

Whole Body ◽

Gaze Control

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