Learning to Move with Affordance Maps

William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan

Abstract: We address the task of autonomous exploration and navigation using spatial affordance maps that can be learned in a self-supervised manner, these outperform classic geometric baselines while being more sample efficient than contemporary RL algorithms