An online gait adaptation with SuperBot in sloped terrains

Abstract

Abstract-Among the different types of robots, modular and self-reconfigurable robots such as SuperBot have less limitations than their counterparts due to their versatility of gaits and increased dynamic adaptability. This results in a highly dexterous and adjustable robot suitable for many environments. This however, usually comes at the expense of a necessary human observer required to monitor and control the robot manually resulting in a waste of power and time. Thus, an intelligent system would be indispensable in optimzing the behavior and control of modular and self-reconfigurable robots. This paper presents an Intelligent Online Reconfiguration System (IORS) which through a combination of learning and reasoning, increases the efficiency in control and movement of the modular and self-reconfigurable robot called Superbot. Using this system, Superbot is able to learn and choose the best gait automatically by sensing its current environment (e.g., friction or slope). As a result, the IORS implementation in SuperBot achieves: 1) correct slope gradient sensing, 2) best gait learning to traverse different slopes, and 3) rational decision making for choosing the best gait.

Lane detection & localization for UGV in urban environment

“…Next, we implement the Mutual-Expectation to choose two points, SP left and SP right , in the two classes as shown as in Table I. This is because that the Mutual-Expectation (ME) [9] is efficient to find the best answer given noisy data-sets if and only if each data-set represents different information, but are related each other. .…”

M-blocks: Momentum-driven, magnetic modular robots

“…While research in chain-based modular robots is quite active [3], [4], focus has shifted away from lattice-based approaches based on the SCM model. If we expect latticebased self-reconfigurable systems to remain an active area of research, we should move past the sliding cube model and all of its practical limitations.…”

A Multi-Sensory Autonomous Docking Approach for a Self-Reconfigurable Robot without Mechanical Guidance

“…SRR was first proposed by Fukuda, i.e., the CEBOT [1]. Since the initial conception, many other SRR systems, including Roombot [2][3][4], M-Cube [5], M-TRAN [6][7][8][9][10], ModRED [11], SuperBot [12][13][14] and Yamor [15][16][17], to name only a few, have been developed. Current docking algorithms are based on either infrared sensing or vision.…”