论文标题
CLIO:一种新型的机器人解决方案,用于在敌对山区环境中探索和救援任务
CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments
论文作者
论文摘要
标准的机器人可以实现山区环境中的救援任务,因为高斜坡或飞行机器人可以通过有限的有效载荷能力来实现。我们提出了一个绳索攀岩机器人的概念,该机器人可以谈判前进的斜坡并携带繁重的有效载荷。机器人通过绳子固定在山上,并配备了一条腿来推向山上并开始跳跃动作。在跳跃之间,提升机被用来绕/放开绳索,以垂直移动并影响横向运动。这种简单(但有效)的两倍致动,使系统能够达到高安全性和能源效率。确实,绳索可以防止机器人在补偿大部分重量的同时大大减少腿部执行器所需的努力。我们还提出了一种最佳控制策略,以生成克服障碍的点对点轨迹。由于使用自定义简化的机器人模型,我们可以实现快速的计算时间(<1 s)。我们使用完整的机器人模型验证了凉亭模拟中生成的最佳运动,在16 m的跳远上误差<5%,显示了拟议方法的有效性,并确认了我们概念的兴趣。最后,我们进行了可及性分析,表明可实现的目标区域受脚壁接触的摩擦特性的强烈影响。
Rescue missions in mountain environments are hardly achievable by standard legged robots-because of the high slopes-or by flying robots-because of limited payload capacity. We present a concept for a rope-aided climbing robot which can negotiate up-to-vertical slopes and carry heavy payloads. The robot is attached to the mountain through a rope, and it is equipped with a leg to push against the mountain and initiate jumping maneuvers. Between jumps, a hoist is used to wind/unwind the rope to move vertically and affect the lateral motion. This simple (yet effective) two-fold actuation allows the system to achieve high safety and energy efficiency. Indeed, the rope prevents the robot from falling while compensating for most of its weight, drastically reducing the effort required by the leg actuator. We also present an optimal control strategy to generate point-to-point trajectories overcoming an obstacle. We achieve fast computation time (<1 s) thanks to the use of a custom simplified robot model. We validated the generated optimal movements in Gazebo simulations with a complete robot model with a < 5% error on a 16 m long jump, showing the effectiveness of the proposed approach, and confirming the interest of our concept. Finally, we performed a reachability analysis showing that the region of achievable targets is strongly affected by the friction properties of the foot-wall contact.