Abstract
Collision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.
Highlights
Current state-of-the-art surgical systems provide stereo vision and tele-operated robotic control of instruments to enable highly dexterous surgical actions in small spaces
We mainly focused on the collision detection between OBBs, which applied to the robot-assisted medical surgery
Our result indicated that the proposed algorithm and the parallel, fully pipelined architecture on our Field-programmable gate array (FPGA) platform are very promising for applications in image-guided, haptic-enabled robotic surgery
Summary
Current state-of-the-art surgical systems provide stereo vision and tele-operated robotic control of instruments to enable highly dexterous surgical actions in small spaces. A promising alternative to hardware sensing is to provide simulated haptic feedback based on potential collision/ contact between image-based anatomical models and surgical instruments (Gibson et al, 1997; Bethea et al, 2004; Meijden and Schijven, 2009; Okamura, 2009; Kwok et al, 2013). The virtual complex-shape objects at the surgical site will have to be decomposed and generalized into numerous primitives, such as spheres and boxes. After that, these uniform geometric representations are effectively parallelized in order to maintain smooth and continuous haptics at a rate above 1 kHz (Basdogan et al, 2004). This 1 kHz rate is the recognized requirement for providing smooth and continuous haptics during the medical surgery
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