Wielding¹（使用，挥舞） two claws, a motor and a tail that swings like a grandfather clock's pendulum²（钟摆） , a small robot named ROCR ("rocker") scrambles³ up（迅速爬上，拼凑） a carpeted, 8-foot wall in just over 15 seconds – the first such robot designed to climb efficiently⁴ and move like human rock climbers or apes swinging through trees. "While this robot eventually can be used for inspection⁵, maintenance（维修，保持） and surveillance, probably the greatest short-term potential is as a teaching tool or as a really cool toy," says robot developer William Provancher, an assistant professor of mechanical engineering at the University of Utah.

His study on development of the ROCR Oscillating Climbing Robot is set for online publication this month by Transactions on Mechatronics, a journal of the Institute of Electrical and Electronics Engineers and American Society of Mechanical Engineers.

Provancher and his colleagues wrote that most climbing robots "are intended for maintenance or inspection in environments such as the exteriors⁶（外部，表面） of buildings, bridges or dams, storage tanks, nuclear facilities or reconnaissance（侦查，勘测） within buildings."

But until now, most climbing robots were designed not with efficiency in mind, only with a more basic goal: not falling off the wall they are climbing.

"While prior climbing robots have focused on issues such as speed, adhering to（坚持，粘附） the wall, and deciding how and where to move, ROCR is the first to focus on climbing efficiently," Provancher says.

One previous climbing robot has ascended⁷ about four times faster than ROCR, which can climb at 6.2 inches per second, but ROCR achieved 20 percent efficiency in climbing tests, "which is relatively⁸ impressive given that a car's engine is approximately 25 percent efficient," Provancher says.

The robot's efficiency is defined as the ratio of work performed in the act of climbing to the electrical energy consumed by the robot, he says.

Provancher's development, testing and study of the self-contained robot was co-authored by Mark Fehlberg, a University of Utah doctoral student in mechanical engineering, and Samuel Jensen-Segal, a former Utah master's degree student now working as an engineer for a New Hampshire company.

The National Science Foundation and University of Utah funded the research.