In this talk I will present an active visual tracker with collision avoidance for camera-equipped robots in dense multi-agent scenarios. The objective of each tracking agent (robot) is to maintain visual fixation on its moving target while updating its velocity to avoid other agents. However, when multiple robots are present or targets intensively intersect each other, robots may have no accessible collision-avoiding paths. We address this problem with an adaptive mechanism that sets the pair-wise responsibilities to increase the total accessible collision-avoiding controls. The final collision-avoiding control accounts for motion smoothness and view performance, i.e. maintaining the target centred in the field of view and at a certain size. Experimental results with real people trajectories from public datasets show that the proposed method improves view maintenance.
Escuela Politécnica Superior | Universidad Autónoma de Madrid | Francisco Tomás y Valiente, 11 | 28049 Madrid | Tel.: +34 91 497 2222 | e-mail: informacion.eps@uam.es
