We invite researchers to contribute original research articles as well as review articles that will stimulate new results in robot perception based on visual or/and tactile data The goal of this special issue is to explore the challenges and solutions to improve robot perception in indoor and outdoor environments. In this context, the sensing techniques are essential to allow robots to perform tasks autonomously (i.e., semantic perception from visual/tactile sensors, mapping and exploration for mobile robots, recognition, location and/or assessment of object properties, intelligent manipulation, grasp planning and manipulation learning from visual/tactile data, data-driven control based on visual/tactile sensing, etc.). In recent years, research and studies have sought new approaches or improvements of known methods and algorithms to achieve a robust sensing of dynamic and complex environments of the real world.

Potential topics include but are not limited to the following:

• Image sensing (sight):
  • Novel sensors and technologies for data recovery of an environment for robotic perception
  • Novel filtering, processing, keypoints, and features estimation for 2D/3D image processing in applications with robots
  • Segmentation and surface modelling for object recognition in tasks with robots
  • Object recognition and pose estimation for grasping tasks, intelligent manipulation, and other tasks with robots
  • Environment reconstruction and mapping for robot navigation
  • Integration and sensorial fusion among vision sensors and others to improve the accuracy and robustness of sensing robots
  • Learning methods and techniques based on deep learning for environment and object recognition and interpretation to be able to get smart robots
• Force and tactile sensing (touch):
  • Novel sensor and technologies that enhance pressure perception such as flexible tactile and artificial skins
  • Data processing and techniques used by force, pressure, and tactile systems for capturing physical properties of the environment such as shape, material, or texture of objects
  • Algorithms for autonomous calibration and learning in dynamic environments
  • Interpretation of tactile data for high level cognition for the interaction with dynamic environments in grasping tasks, intelligent manipulation, and so forth
  • Control strategies and algorithms using force and tactile sensors for humanoid, robotic prostheses, hand and arm robots, and so forth