Visual sensing for developing autonomous behavior in snake robots

Snake robots are uniquely qualified to investigate a large variety of settings including archaeological sites, natural disaster zones, and nuclear power plants. For these applications, modular snake robots have been tele-operated to perform specific tasks using images returned to it from an onboard camera in the robots head. In order to give the operator an even richer view of the environment and to enable the robot to perform autonomous tasks we developed a structured light sensor that can make three-dimensional maps of the environment. This paper presents a sensor that is uniquely qualified to meet the severe constraints in size, power and computational footprint of snake robots. Using range data, in the form of 3D pointclouds, we show that it is possible to pair high-level planning with mid-level control to accomplish complex tasks without operator intervention.

[1]  Srinivasa G. Narasimhan,et al.  A low-power structured light sensor for outdoor scene reconstruction and dominant material identification , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[2]  Alonzo Kelly,et al.  Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments , 2006, Int. J. Robotics Res..

[3]  Howie Choset,et al.  Parameterized and Scripted Gaits for Modular Snake Robots , 2009, Adv. Robotics.

[4]  Shigeo Hirose,et al.  3 axial force sensor for a semi-autonomous snake robot , 2009, 2009 IEEE International Conference on Robotics and Automation.

[5]  Howie Choset,et al.  Virtual chassis for snake robots , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  A. Kuzucu,et al.  Design and control of biologically inspired wheel-less snake-like robot , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[7]  Shigeo Hirose,et al.  Snakes and Strings: New Robotic Components for Rescue Operations , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

[8]  Howie Choset,et al.  Simplified motion modeling for snake robots , 2012, 2012 IEEE International Conference on Robotics and Automation.

[9]  Shigeo Hirose,et al.  Biologically Inspired Snake-like Robots , 2004, 2004 IEEE International Conference on Robotics and Biomimetics.

[10]  Howie Choset,et al.  Conical sidewinding , 2012, 2012 IEEE International Conference on Robotics and Automation.

[11]  Ross A. Knepper,et al.  Snakes on a plan: Toward combining planning and control , 2013, 2013 IEEE International Conference on Robotics and Automation.

[12]  Avinash C. Kak,et al.  Modeling and calibration of a structured light scanner for 3-D robot vision , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[13]  Howie Choset,et al.  Design and architecture of the unified modular snake robot , 2012, 2012 IEEE International Conference on Robotics and Automation.

[14]  Howie Choset,et al.  Adaptive Data Confidence Using Cyclical Gaits On A Modular Snake Robot , 2011 .

[15]  Jonathan P. How,et al.  Increasing autonomy of UAVs , 2009, IEEE Robotics & Automation Magazine.

[16]  Pål Liljebäck,et al.  Snake Robot Obstacle-Aided Locomotion: Modeling, Simulations, and Experiments , 2008, IEEE Transactions on Robotics.