Collision Avoidance of 3-Dimensional Objects in Dynamic Environments

Achieving collision avoidance between moving objects is an important objective while determining robot trajectories. In performing collision avoidance maneuvers, the relative shapes of the objects play an important role. The literature largely models the shapes of the objects as spheres, and this can make the avoidance maneuvers very conservative, especially when the objects are of elongated shape and/or non-convex. In this paper, we model the shapes of the objects using suitable combinations of ellipsoids and one-sheeted/two-sheeted hyperboloids, and employ a collision cone approach to achieve collision avoidance. We present a method to construct the 3-D collision cone, and present simulation results demonstrating the working of the collision avoidance laws.

Collaborative Tracking and Capture of Aerial Object using UAVs

This work details the problem of aerial target capture using multiple UAVs. This problem is motivated from the challenge 1 of Mohammed Bin Zayed International Robotic Challenge 2020. The UAVs utilise visual feedback to autonomously detect target, approach it and capture without disturbing the vehicle which carries the target. Multi-UAV collaboration improves the efficiency of the system and increases the chance of capturing the ball robustly in short span of time. In this paper, the proposed architecture is validated through simulation in ROS-Gazebo environment and is further implemented on hardware.