Research in autonomous mobile manipulation aims to develop mobile robotic systems with manipulation capabilities to perform complex tasks in dynamic, unstructured, and field environments, in which task-tailored design, control, and novel application methods are required. Some widely used applications include, but not limited to, logistic, industrial maintenance, remote medical examination, and service robotic tasks. For this purpose, autonomous mobile manipulation systems should be able to perform and coordinate different skills, such as locomotion, perception, manipulation and grasping.
To acquire more advanced autonomy and operate within the real world, such systems should be further investigated with the following capacities: (1) generality and be adaptive across unseen tasks; (2) perceiving their environments via sensors that typically deliver high-dimensional data with low response latency and energy efficiency; (3) traveling in challenging scenarios and performing complex tasks with uncertainty; (4) great system stability and complexity to integrate many hardware components as well as software algorithms for different functionalities.
In nature, biological intelligence has great capabilities and generalities to locomote, perceive, and act in the real world exceptionally well and outperforms state-of-the-art robots in almost every aspect of life. Nowadays, more and more works are investigating biological-inspired for robotic studies in many areas, ranging from biomimetic mechanical design of robots, neuromorphic sensing and computing to brain-inspired navigation. This research topic seeks to invite theoretical and experimental results dealing with biological-inspired and conventional techniques for the design, control, and real-world applications for autonomous mobile manipulation systems. Specifically, this research topic investigates interdisciplinary innovation in many areas of robots, such as information perception, novel control architectures, biomimetic mechanism, motion planning, grasping and manipulation, human-robot interaction, and artificial intelligence and machine learning. We welcome research articles, reviews, datasets or benchmarks tested in real-world applications.
Topics of interest include, but are not limited to:
• Biomimetic mechanical design of novel autonomous mobile manipulation systems.
• Task-tailored design, control, and real-world applications for autonomous mobile manipulation
• Biological-inspired control architecture for autonomous mobile manipulation
• Neuromorphic sensing and data fusion for handling high-dimensional state spaces for autonomous mobile manipulation
• Biological-inspired motion planning methods for co-control of manipulation and mobile locomotion.
• Biological-inspired learning for grasping, manipulation, and navigation skills.
• Mapping and localization
• Benchmarking and datasets on autonomous mobile manipulation in real-world experiments