A review of terrain detection systems for applications in locomotion assistance

• Published in: Robotics and autonomous systems Vol. 133; p. 103628
• Main Authors: Al-dabbagh, Ali H.A., Ronsse, Renaud
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2020
• Subjects: Environmental features recognition; Human locomotion assistance; Intent detection; Locomotion modes prediction; Prostheses; Ramp detection; Stairs detection; Terrain detection systems; Vision; Visually impaired; Wearable sensors; Ramp detection; Prostheses; Stairs detection; Locomotion modes prediction; Visually impaired; Environmental features recognition; Vision; Terrain detection systems; Human locomotion assistance; Intent detection; Wearable sensors
• ISSN: 0921-8890; 1872-793X
• DOI: 10.1016/j.robot.2020.103628

Terrain detection systems have been developed for a large body of applications. For instance, a bionic leg prosthesis would have to adapt its behavior as a function of the terrain, in order to restore a sound lower-limb biomechanics to the amputee. Visually impaired people benefit from such systems in order to collect information about their locomotion environment and avoid obstacles. Finally, mobile robots use them for estimating terrain traversability, and adjusting control algorithms as a function of the surface type. This diversity of applications led to a large repertoire of systems, regarding both hardware (sensors, processing unit) and software used for classification. This paper provides an extended review of these systems, with a specific focus on the assistance of disabled walker. More precisely, it overviews the sensory systems and algorithms that were implemented to identify different locomotion terrains in indoor or urban environments (flat ground, stairs, slopes) in a way that they are or can be worn by a human user, and running in real-time. Contributions from mobile robotics are also included, pending that they could be adapted to a scenario of locomotion assistance. The systems are classified into two categories: these relying on proprioceptive sensors only and those further using exteroceptive sensors. Contributions from both categories are then compared according to their main specifications, such as accuracy and prediction time. The paper unambiguously shows that systems with exteroceptive sensors have higher prediction capability than systems with proprioceptive sensors only, and should thus be favored for assistive devices requiring predicting transitions between locomotion tasks. [Display omitted] •This paper provides an extended review of terrain detection systems for disabled people assistance (lower limb amputees and visually impaired).•It overviews the sensory systems and algorithms that were implemented to identify different locomotion terrains in indoor or urban environments (flat ground, stairs, slopes).•Reviewed approaches are those that can be worn by a human user, and running in real-time.