Viability of commercial depth sensors for the REX medical exoskeleton : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Albany, New Zealand
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Date
2016
Open Access Location
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Massey University
Abstract
Closing the feedback loop of machine control has been a known method for gaining stability.
Medical exoskeletons are no exception to this phenomenon. It is proposed that through machine
vision, their stability control can be enhanced in a commercially viable manner. Using machines
to enhance human’s capabilities has been a concept tried since the 19th century, with a range of
successful demonstrations since then such as the REX platform. In parallel, machine vision has
progressed similarly, and while applications that could be considered to be synonymous have been
researched, using computer vision for traversability analysis in medical exoskeletons still leaves a
lot of questions unanswered. These works attempt to understand better this field, in particular,
the commercial viability of machine vision system’s ability to enhance medical exoskeletons.
The key method to determine this will be through implementation. A system is designed that
considers the constraints of working with a commercial product, demonstrating integration into
an existing system without significant alterations. It shows using a stereo vision system to gather
depth information from the surroundings and amalgamate these. The amalgamation process
relies on tracking movement to provide accurate transforms between time-frames in the threedimensional
world. Visual odometry and ground plane detection is employed to achieve this,
enabling the creation of digital elevation maps, to efficiently capture and present information
about the surroundings. Further simplification of this information is accomplished by creating
traversability maps; that directly relate the terrain to whether the REX device can safely navigate
that location. Ultimately a link is formed between the REX device and these maps, and that
enables user movement commands to be intercepted. Once intercepted, a binary decision is
computed whether that movement will traverse safe terrain. If however the command is deemed
unsafe (for example stepping backwards off a ledge), this will not be permitted, hence increasing
patient safety. Results suggest that this end-to-end demonstration is capable of improving patient
safety; however, plenty of future work and considerations are discussed. The underlying data
quality provided by the stereo sensor is questioned, and the limitations of macro vs. micro
applicability to the REX are identified. That is; the works presented are capable of working on a
macro level, but in their current state lack the finer detail to improve patient safety when operating
a REX medical exoskeleton considerably.
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Keywords
Robotic exoskeletons, Design and construction, Detectors, Computer vision, Depth perception, Robotics in medicine